Minimum Partition of Polygons Under Width and Cut Constraints
Abstract
We study the problem of partitioning a polygon into the minimum number of subpolygons using cuts in predetermined directions such that each resulting subpolygon satisfies a given width constraint. A polygon satisfies the unit-width constraint for a set of unit vectors if the length of the orthogonal projection of the polygon on a line parallel to a vector in the set is at most one. We analyze structural properties of the minimum partition numbers, focusing on monotonicity under polygon containment. We show that the minimum partition number of a simple polygon is at least that of any subpolygon, provided that the subpolygon satisfies a certain orientation-wise convexity with respect to the polygon. As a consequence, we prove a partition analogue of the Bang’s conjecture about coverings of convex regions in the plane: for any partition of a convex body in the plane, the sum of relative widths of all parts is at least one. For any convex polygon, there exists a direction along which an optimal partition is achieved by parallel cuts. Given such a direction, an optimal partition can be computed in linear time.
Keywords and phrases:
Polygon partitioning, Width constraints, Plank problemFunding:
Jaehoon Chung: Supported by a KIAS Individual Grant AP106101 via the Center for Artificial Intelligence and Natural Sciences at Korea Institute for Advanced Study.Copyright and License:
2012 ACM Subject Classification:
Theory of computation Computational geometryEditors:
Ho-Lin Chen, Wing-Kai Hon, and Meng-Tsung TsaiSeries and Publisher:
Leibniz International Proceedings in Informatics, Schloss Dagstuhl – Leibniz-Zentrum für Informatik
1 Introduction
Most works in partitioning polygons have primarily focused on maximizing geometric measures, such as fatness or the minimum side length of resulting pieces [11, 13, 20]. In this paper, we study an opposite objective: partitioning a polygon into subpolygons whose widths are bounded above in certain directions. Such a width constraint commonly arises in manufacturing and recycling industries, where materials must be cut or processed within certain width limits. For example, wood chipping and metal shredding require pieces to fit within the machine’s inlet. In some materials, cut directions are critical for preserving structural strength; for example, fabric is typically cut along the fiber direction [17].
Our problem is rooted in classical questions in convex geometry, notably Tarski’s plank problem and its affine-invariant extension by Bang [7]. The original conjecture asserts that any covering of a convex body in by strips must have a total width at least the minimal width of the body, which was proven by Bang. Bang further proposed the affine plank problem, in which strip widths are measured relative to the body’s width in the same direction. The affine version remains open in general, with only partial results [16, 4, 19, 6]. It is known to be equivalent to the Davenport conjecture [5], which concerns partitions. Several partition analogues have been studied [9, 3, 10].
Our work can also be viewed as a partition analogue of these problems in the plane, where width constraints replace strips, and simple polygons substitute convex bodies.
1.1 Problem definition and results
We consider the problem of partitioning polygons into the minimum number of pieces satisfying both a unit-width constraint and a cut constraint. Let be a simple polygon. Let be a piece in a partition of satisfying unit-width constraint , where is the set of unit vectors . Let denote the width of in , that is, the length of the orthogonal projection of on a line parallel to . We say satisfies the unit-width constraint if for some vector .
The process of partitioning must satisfy a cut constraint . A cut is defined as a line segment within whose relative interior lies in the interior of . A unit vector is often used to represent a direction, such as the orientation of a cut, meaning that the cut lies on a line parallel to the vector. We require that every cut must be in a direction in . If a cut extends from one edge of to the other edge, it divides into two distinct pieces; such a cut is called a guillotine cut. A guillotine partition of (also called a binary partition) is obtained by a finite sequence of guillotine cuts; it starts from and recursively partitions each piece into two subpieces using a guillotine cut. A non-guillotine partition of is an arbitrary partition of using cuts that are not necessarily guillotine. Figure 1 shows a guillotine partition and a non-guillotine partition.
Given a simple polygon , our objective is to partition into the minimum number of pieces using cuts constrained by such that each piece in the partition satisfies unit-width constraint . We denote this minimum partition problem by and its optimum value by . Throughout this paper, we use and exclusively to refer to the unit-width constraint and the cut constraint, respectively.
Related Work.
Damian and Pemmaraju [14] and Damian-Iordache [15] gave a polynomial-time algorithm for partitioning a simple polygon into the minimum number of subpolygons without using Steiner points such that each subpolygon has diameter at most , for . Later, Buchin and Selbach [11] showed that this problem becomes NP-hard for polygons with holes. Worman [22] proved NP-completeness for a variant in which each subpolygon must be contained in an axis-aligned square of side length . Abrahamsen and Stade [2] showed that allowing Steiner points leads to NP-hardness for the partition problem under axis-aligned unit-square containment, even for simple polygons without holes. This marks the first known NP-hardness result of the minimum partition problems for hole-free polygons. Abrahamsen and Rasmussen [1] studied the problem of partitioning simple polygons into the minimum number of pieces such that each piece satisfies a bounded-size constraint (e.g., unit area, perimeter, diameter, or containment within unit disks or squares).
Our Results.
Our main contribution is an analysis of the minimum partition number under constraints . First, we provide necessary and sufficient conditions for the existence of feasible partitions in , along with a decision algorithm for testing feasibility
Second, we study the monotonicity of the minimum partition number under polygon containment (Sections 3, 4, and 5). We show that this monotonicity does not hold in general, and identify a sufficient condition based on a restricted-orientation convexity, called -convexity, where . Theorem 3 states that holds if is -convex with respect to for guillotine partitions, or -convex with respect to for non-guillotine partitions, where is the set of all unit vectors perpendicular to those in .
Finally, we prove a partition analogue of Bang’s conjecture (Section 6). The statement of Bang’s conjecture is as follows: if a convex body is covered by strips , then . Our theorem replaces strip coverings with arbitrary partitions and extends the direction set to any subset .
Theorem 1 (Bang-Type Partition Analogue).
Let be a convex body, and let be its arbitrary partition. Then, for any subset ,
To the best of our knowledge, this is the first partition analogue that allows non-convex pieces. We also show that, for , an optimal partition of a convex polygon can be computed in linear time using equally spaced parallel cuts (See Corollary 17). The omitted proofs will be found in the full version of the paper at https://arxiv.org/abs/2509.09981.
2 Preliminaries
Let be a simple polygon with vertices in the plane. We assume that the vertices of are given in a list sorted in counterclockwise order along its boundary. A partition of a simple polygon is a set of connected pieces with pairwise disjoint interiors whose union equals the polygon. The cardinality of a partition is the number of its pieces.
For a set , we denote by the boundary of , by the interior of , and by the closure of . We treat a polygon as the union of its interior and boundary; , is the boundary, and is the interior.
For a point , let and be its - and -coordinates, respectively. For any two points and in , we use to denote the line segment connecting and with length . We call a cut in if it lies entirely in the interior of , excluding its endpoints. If both endpoints lie on , we call it a guillotine cut.
The inner product of any two vectors and is denoted by . The Euclidean norm of a vector is denoted by . A vector with norm 1 is called a unit vector. We use to denote the set of unit vectors . For a subset , we define .
For a compact set and a vector , let denote the length of the orthogonal projection of on a line parallel to . We say satisfies unit-width constraint if and only if for some .
A strip is the region in the plane bounded by two parallel lines. The distance between the bounding lines is the width of the strip, and the direction in orthogonal to the bounding lines is called the normal vector of this strip. If a strip has width 1, we call it a unit strip.
We use the notation for a positive integer . For a finite set , we use to denote the cardinality of which is the number of its elements.
3 Monotonicity of minimum partition numbers
In this section, we assume that has a partition satisfying the constraints. The necessary and sufficient condition for feasibility is presented in the full version. We show for any subpolygon of that satisfies a certain condition. For both guillotine and non-guillotine partitions, we identify sufficient conditions on that ensure this monotonicity. When the constraints and are clear from context, we abbreviate as .
Let be a square of side length 2, and let be a subpolygon of as shown in Figure 2(a). Consider the instance with and . Since is a singleton, every cut must be a guillotine cut. Observe that neither nor satisfies unit-width constraint . A vertical cut halving yields a feasible partition of two pieces. No vertical cut, however, in partitions into two pieces, each with horizontal width at most 1. Thus, , implying that the inclusion alone is not sufficient to ensure .
Such failures are common in minimum partitioning problems, as the optimal partition number depends on the geometric complexity of . Two typical approaches are restricting the geometry of relative to , and constraining the partition class to specific families, such as the guillotine (binary) class [9]. These alter the structural properties of feasible solutions.
3.1 Restricted-orientation convexity
Rawlins [21] introduced the restricted-orientation convexity as a generalization of standard convexity in Euclidean space. For , a set is -convex if, for every line parallel to a vector in , is connected (we regard an empty set as being connected). When , -convexity coincides with standard convexity in . We extend this concept to subpolygons of simple polygons with respect to guillotine cuts.
Definition 2.
Let be a subpolygon of a polygon , and be a set of unit vectors. Then is -convex with respect to if its intersection with every guillotine cut in parallel to a vector in is connected.
Figure 2(c) shows a subpolygon that is -convex with respect to for , but not -convex for since a guillotine cut in parallel to intersects in at least two connected components.
Observe that -convexity with respect to a polygon is equivalent to the geodesic convexity within when . The following theorem gives sufficient conditions for monotonicity of the minimum partition numbers.
Theorem 3 (Monotonicity in Polygon Containment).
Let and be sets of unit vectors, and let be a subpolygon of a polygon . Assume that has a solution.
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for guillotine partitions if is -convex with respect to .
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for non-guillotine partitions if is -convex with respect to .
Revisit the subpolygons in Figure 2(a,b). In (a), is neither -convex nor -convex with respect to , whereas in (b), satisfies both conditions, and Theorem 3 implies that , for both guillotine and non-guillotine partitions.
3.2 Monotonicity in guillotine partitions
We prove Theorem 3 for the guillotine case. Let be a guillotine partition of feasible to , and let be its restriction to a subpolygon that is -convex with respect to . Then, , and thus, also forms a partition of . Note that each piece in satisfies unit-width constraint , as every piece is a subset of some that satisfies the constraint. To show , it suffices to verify two aspects: (1) is a guillotine partition of and (2) .
Since is a guillotine partition, the cuts used for are partially ordered by their precedence in the partitioning process. Let denote a sequence of guillotine cuts that produces . Then each is connected as is a cut in with a direction in and is -convex with respect to . Let be the subsequence of consisting of those satisfying for . Note that each for is a cut in and . Also, observe that is induced by . It suffices to show that is indeed a sequence of guillotine cuts in : each is a guillotine cut in one subpolygon obtained by applying to .
Let be the smallest index in such that . Since no cut in intersects , there is a subpolygon in the partition of by that contains . Observe that is a guillotine cut in this subpolygon that is aligned with a direction in . Since is -convex with respect to , is a line segment, and thus, is a guillotine cut in .
We proceed by induction on with , that forms a sequence of guillotine cuts in . Among the pieces of partitioned by the sequence, let denote the one containing , where is a cut in . By definition, there exists an index such that . Let be the piece in the partition of by that contains .
To see that is a guillotine cut of , recall that , where is a guillotine cut of and . Let be the guillotine cut in obtained by extending until it touches . Since is -convex, is connected, and hence so is its subsegment . Moreover, as spans , its restriction to necessarily touches at both endpoints. Thus, is a guillotine cut in . We conclude that induces a guillotine partition of . Since , we have .
Lemma 4.
Let be a polygon and let be a solution to the problem for guillotine cuts. If a subpolygon of is -convex with respect to , the restricted partition is a solution to for guillotine cuts with at most pieces.
4 Reconfiguration of restricted non-guillotine partitions
Let be a subpolygon of that is -convex with respect to . The monotonicity trivially holds when . Also, any feasible partition is guillotine when is a singleton. Assume that and contains at least two distinct vectors.
Let be any feasible partition of to . Its restriction to , defined as , is a feasible partition of to . However, some regions may be disconnected, even when is -convex with respect to (See Figure 3(a–b)). To address this, we modify the cuts in to reconnect disjoint fragments into connected regions while preserving feasibility for .
Consider any element in the partition of such that . The intersection consists of open connected components. We define as
Let . Note that each is a subpolygon of with positive area that touches . To connect elements in into a single piece, we reconfigure by iteratively performing a process, called reallocation. Let be a connected region in . We define the reallocation of to as the operation that modifies by expanding the region assigned to so that it includes . This can be done by adding new boundaries along and removing those along . If and intersect in their interiors, or share a boundary segment of positive length, then appears as a single piece in the resulting partition. We say that the region is reallocated to .
4.1 Construction and layering of corridor of
We first construct a narrow corridor along . This corridor lies entirely within , closely following , and provides the space needed to link elements of .
The corridor is an annular region bounded by two simple closed curves: the outer curve and an inner curve that lies at a small distance inward. The region between the two curves is called the -corridor of , where denotes its width. In our construction, we set to be a sufficiently small positive value and denote the resulting corridor by .
Consider the edges of each that have one endpoint on and intersect . Let denote the set of such edges of . We define and . The corridor is subdivided into a sequence of nested subregions, which we refer to as layers. Let denote the number of layers which will be determined in Section 4.4. For each , we construct a simple closed curve lying entirely within , such that the curves are pairwise disjoint and arranged sequentially inward from . Each follows a zigzag pattern using the two directions in , and intersects every edge in once or twice, depending on whether the edge is a guillotine cut in . Details on the construction of the corridor and simple curves are provided in the full version.
These curves subdivide into nested subregions, called layers: for each , the -th layer is the annular region bounded by and , where we define .
4.2 Link instructions with circular intervals and layers
Let and be two elements in with . For , let denote the -th layer. Each connected component of for is a subregion of referred to as a layer segment of (and of ) in . Each layer segment is bounded by four parts: continuous portions of the inner and outer boundaries of , and two edges from . Removing any layer segment from alters its topological structure from an annulus to a weakly simple polygon. All layer segments in can be arranged in cyclic order along . Figure 4(a) illustrates a layer segment of in .
We use an interval notation over layer segments that are cyclically ordered. For two layer segments in , we denote by the set of layer segments encountered in counterclockwise traversal from to in , where . Similarly, , , and denote the open and half-open intervals over layer segments between and in .
Assume that and are layer segments of in , for with . The reallocation of to merges and into a single piece within . We refer to such an ordered pair as a link instruction of . See Figure 4(b–c).
Decomposition of into circular intervals.
For , is a subpolygon of that touches . The intersection consists of continuous paths on . Specifically, it can be the loop itself if , implying that satisfies unit-width constraint . However, assuming , this case does not occur. Thus, every connected component of must be a continuous path on that is not a loop. We define as
We then define the aggregate sets and .
Let be a continuous path along with endpoints and such that corresponds to the portion of from to in counterclockwise order. Since is a simple closed curve, topologically equivalent to a circle, we regard each path as a circular interval on . As contains no loops, the case occurs only when touches at a single point , and no other portion of near intersects . Such intervals are called degenerate intervals.
For , may contain both degenerate and non-degenerate intervals. Since is simple, all intervals in are pairwise interior-disjoint. Figure 5(a) shows a piece and the subpolygon , from which the circular intervals in are defined. These intervals are illustrated in Figure 5(b).
Note that a degenerate interval at some point may appear in multiple ’s. In such cases, each occurrence is treated as a distinct element in . Since is a partition of and , every point on belongs to some interval of , and no two intervals in intersect each other in their interiors. Thus, forms a decomposition of .
Finally, we relate these circular intervals to layer segments so as to define a link instruction formally. For any and any , consider the component and the layer . Each connected component of (or ) is bounded by four parts: continuous portions of the inner and outer boundaries of (or ), and two edges from . Each connected component of is entirely contained within a unique connected component of . Moreover, the portion of that bounds each connected component of corresponds to a circular interval in . Thus, each layer segment of in is uniquely associated with a circular interval in , in a one-to-one correspondence. The number of layer segments in (or ) is (or ).
We revisit the link instruction that merges two layer segments and for along layer . The link instruction reallocates the region in spanned counterclockwise from to . Since and correspond to circular intervals in and , respectively, each link instruction can be represented by a triple , where and (See Figure 4). Note that , as the counterclockwise span from to differs from that in the reverse order.
4.3 Graph for encoding link instructions
Recall that is the set of closures of connected pieces of such that each has a positive area and touches . We construct a graph for each , which specifies how the elements of are to be connected into a single piece within .
For each , consists of circular intervals, each corresponding to a continuous path in along . Let denote the subset of consisting of only those intervals with positive length. We define and . Unlike , the set contains only non-degenerate intervals, which are pairwise interior-disjoint. Note that forms a partition of .
Sequencing subpaths of .
For each , consists of connected components, each forming a continuous path connecting two points on . By the definition of , the endpoints of these paths correspond to the endpoints of the circular intervals in . The total number of such paths in is . See Figure 5(a).
We traverse counterclockwise, starting at any point on and completing a full circuit. During the traversal, each path in is visited exactly once for each , except for the path containing the starting point. The order in which the continuous paths are visited is denoted by , where is the path in containing the starting point, and .
Consider two consecutive paths and for any . Each path is derived from some piece in ; there exist such that and . As we traverse from to , we exit through an endpoint of and re-enter through an endpoint of .
Lemma 5.
Let be a pair of consecutive paths for , where and for some . The traversal from to exits and re-enters through intervals and , respectively. If , then . Otherwise, and are interior-disjoint, non-degenerate intervals.
By Lemma 5, a pair of distinct intervals in provides an exit-entry pair for each transition between distinct pieces in in the counterclockwise traversal of .
Construction of .
Based on the counterclockwise traversal of , we construct a directed graph as follows. Each vertex corresponds to an interval in , so . Let and be consecutive paths in the traversal where and with . The traversal from to encounters intervals and in that contain the exit and entry points, respectively. By Lemma 5, these intervals and are uniquely determined. We add a directed edge between vertices and corresponding to and , respectively.
Let and denote the exit and entry points of the traversal, respectively; is the endpoint of and is the endpoint of . The counterclockwise traversal on between and follows a simple path along outside that starts from and ends at . Let denote this path from to . Observe that the exit and entry points may coincide, i.e., , if and are adjacent at and lies counterclockwise from along . In this case, the direction of is assigned from to .
Given that , the simple path can be viewed as a simple path connecting two distinct points on the boundary of the circle and lying outside the circle. The path can be classified into one of two types, depending on how it winds around the circle. Formally, is homotopic to a directed path in that winds around in either counterclockwise or clockwise direction. Note that it cannot wind around the boundary more than once since is simple. We assign the direction of from to if the path is of the counterclockwise type, and from to , otherwise. Figure 5(b) illustrates for both cases where and . The same rule is applied to assign directions to all other edges in .
In summary, we construct the directed graph for to represent how the disjoint components of are to be connected into a single piece within . Each vertex corresponds to an interval in . Each directed edge of represents a link instruction , but is not specified yet. See Figure 5(c) for an illustration of the directed graph that defines three link instructions, where and are as shown in Figure 5(a).
4.4 Layer assignments for link instructions
For , let be the directed graph for . Each edge in represents a link instruction that reallocates layer segments within a specific layer. The goal is to assign layers to link instructions so that no redundant reallocation of layer segments is allowed and all elements in are eventually merged into a single piece for every .
The underlying graph of a digraph is its undirected version, obtained by ignoring the directions of all edges. Consider a connected component of the underlying graph of . We assume that contains more than one vertex, as a component of size 1 does not indicate any link instruction. Each vertex of corresponds to a circular interval in . Let be the subset of such that .
We iteratively perform a combine step to merge all circular intervals in into a single circular interval on . The process begins with an initial set and a circular interval , where is any vertex of and is the circular interval in corresponding to . At each step, any vertex is chosen if there exists an edge between and some vertex . Let be the circular interval corresponding to . We add to and update to be the smallest circular interval on that spans from to in counterclockwise direction if the edge is directed from to , or in clockwise direction otherwise. Once , the process returns a single circular interval on , denoted by , corresponding to the connected component of . See Figure 6(a) for an illustration of this process.
Throughout, we use to denote intervals in and for those in to emphasize their distinct roles. Each is non-degenerate. For any with , there exists a proper containment between and . To prove this, we present a lemma relating connectivity in the underlying graph of to the existence of a path contained in a connected component of , as illustrated in Figure 6(b).
Lemma 6.
The vertices corresponding to and in are connected in the underlying graph of if and only if there is a simple path connecting to contained in .
Let be the set of connected components in . Then each element in is a closed connected set. Moreover, it is a (weakly) simple polygon.
For , let denote the set of all simple paths from to contained in . For , we define . Lemma 6 guarantees the existence of a path between and whenever their corresponding vertices are connected in the underlying graph of . Furthermore, all such paths share a consistent topological behavior, such as winding around in the same direction.
Corollary 7.
Let with . If , then all paths in wind around in the same direction, and there is a unique component that contains all such paths.
Lemma 8.
For any distinct with , or .
By Lemma 8, we construct the circular interval graph , where each node corresponds to a circular interval in , and a directed edge from to is added if for . Then, is acyclic as each edge corresponds to a strict containment.
Transitive reduction of .
The graph represents the transitive closure of the proper containment relation. That is, for , there is a directed edge from to in if there exists some such that and are directed edges in . A transitive reduction of is a directed graph on the same vertex set with the minimum number of edges that preserves all reachability relations of . Since the transitive reduction of a DAG is unique [8], we denote the transitive reduction of by . Let denote the underlying graph of .
Lemma 9.
Any vertex of has out-degree at most one, and is acyclic.
Layer assignment of link instructions.
In each in-branching tree of , the unique vertex with out-degree zero is called the root. The level of a vertex is defined as the number of edges on the path from the root to that vertex plus one, where the level of the root is one. The level of each interval is defined to be the level of the corresponding vertex in .
Recall that each circular interval is formed by merging intervals in for some . These intervals correspond to the vertices of a connected component of , where each edge of encodes a link instruction that merges two elements in . Let denote the set of link instructions corresponding to the edges of . We assign the -th layer to every link instruction in if is at level in . Note that the maximum level in is at most if each connected component of has size two for all . Thus, we set the number of layers in the corridor to this maximum level: .
For each , all link instructions in reallocate layer segments within a single layer to a common piece , where and are determined by . Let such that is the smallest circular interval that spans from to in counterclockwise order. Let be the layer segments corresponding to and , respectively. Applying is equivalent to reallocating every to .
In summary, defines the set of all link instructions for reconfiguration. Applying to yields a partition , where each is a region assigned to within . When is -convex with respect to , each is connected and satisfies both constraints and .
5 Analysis of reconfigured non-guillotine partitions
Assuming that the link instructions in have been applied to in an arbitrary order, we verify the following statements in order to prove Theorem 3.
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(1)
For each , the region allocated to within forms a single connected piece.
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(2)
The reconfiguration of is a solution to the problem if is -convex with respect to .
It follows from statements (1) and (2) that the reconfigured partition of satisfies the constraints and while ensuring that the number of pieces does not exceed .
5.1 Connectivity in reconfigured partitions
For , let denote the subset of consisting of instructions of the form , where and . Then, . We first show that the link instructions in merge all elements of into a single connected piece. We then verify that applying the link instructions in does not disconnect the merged piece. Furthermore, the resulting reconfigured partition of is invariant under the order in which the link instructions in are applied to .
Merging via .
We show that any two pieces are connected by some link instructions in . During the traversal on , each continuous path of is encountered at least once for every , and we denote the sequence of these paths in the order they are visited as , where . Then, there exist indices such that and . Since it is a cyclic sequence with , we assume without loss of generality that .
Recall that an edge of is added whenever two consecutive paths in the sequence are derived from distinct elements in . This indicates that a transition between them occurs during the traversal. The link instruction associated with this edge merges the corresponding elements in . The subsequence contains multiple transitions between distinct elements in , starting from and eventually reaching . Applying all link instructions associated with the transitions in results in and being merged into a single connected piece.
Let denote the subregion of resulting from merging elements of via , with no other instructions applied. Then, consists of all elements in and layer segments reallocated from other pieces: , where is the set of layer segments reallocated to by .
The region denotes the union of all layers in . For each , consists of layer segments within . By construction of layers, is connected and non-empty. We refer to this region as a core of , denoted by . Each consists of its core together with the layer segments it contains. Let denote the set of all layer segments in over all . Therefore, for , we have Figure 7(a) illustrates the parts of : cores and layer segments. The shapes are drawn schematically to reflect the topological structure, rather than an exact polygonal description.
We now turn to the link instructions in that are applied to . Let be a subregion of that is obtained by applying all link instructions in to . Note that any part of reallocated by lies within , and thus the cores remain unchanged. We show that is well-defined, meaning that is invariant under the order in which the instructions in are applied.
Lemma 10.
Let be a link instruction, and let and be the layer segments in corresponding to and , respectively. Then, the layer segments remain assigned to under any link instruction in .
Lemma 10 implies that no layer segment is reassigned by more than one link instruction. As a consequence, we obtain the following corollary, which states that is well-defined.
Corollary 11.
In the reconfiguration of , each layer segment in is reallocated at most once.
Corollary 11 ensures that each layer segment may be reallocated to a different piece at most once, and no chains of reallocations such as with and occur.
This lemma further implies that layer segments in are preserved, while only those in are reallocated by . Let be the subset of that consists of layer segments preserved under . Then, is the subpolygon that is obtained from by removing those layer segments in . Then where . Figure 7(b–c) illustrates the construction of , in which only layer segments in are reallocated by .
Path-Connectivity of .
To prove that forms a connected piece, it suffices to verify two types of path-connectivity among its constituent parts, which must be preserved during the reallocation induced by .
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Each layer segment in is path-connected to some within for .
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The cores are mutually path-connected within .
Here, two sets are said to be path-connected within a region if there exists a path in joining some and .
Lemma 12.
Each layer segment in is path-connected within to the core of some .
By Lemma 12, every layer segment in has a path to some core within . It remains to show that are mutually path-connected within .
Lemma 13.
All cores of elements in are mutually path-connected within .
Remarks.
Applying link instructions in may induce holes within merged pieces in the reconfigured partition of . When contains holes, reallocating them to does not increase for every . Therefore, each can be regarded as a simple polygon.
5.2 Feasibility of reconfigured partitions
We first observe that the reconfigured partition remains as a valid partition of . By construction, the cut constraint is also preserved: each layer segment is bounded by the boundaries of layers and the cuts from , all aligned with directions in . It remains to check the unit-width constraint .
Since is a solution to , there exists a vector such that . In other words, there exists a unit strip with normal vector that contains . If every layer segment reallocated by is contained within , then also satisfies unit-width constraint .
Assume that is a link instruction associated with a directed edge from to in for and . Let be two distinct indices such that and . Recall that the edge between and is added to if and only if there is a transition between and during the counterclockwise traversal on .
For each , let and denote the layer segments in corresponding to and , respectively. The link instruction reallocates the layer segments in to , where and are already assigned to in . We define where It suffices to show that . If this inclusion holds, every layer segment reallocated by lies within , and thus the unit-width constraint is preserved.
Decomposition of .
The region is connected and bounded by four parts: two continuous portions of the inner and outer boundaries of , and two subsegments of edges from and . The outer boundary of is and its inner boundary is , where is the inner -offset polygon of .
For the sake of clarity, we introduce interval notation to represent subpaths of and . For any two points , we denote by the portion of from to in counterclockwise order, including both endpoints. Let , , and . Similarly, we define , and as portions of .
Since and are non-degenerate intervals on , let and for some points with and . The portion of contained in is . Let be the endpoints of the portion of lying on , which we denote by . Finally, the parts of along the edges of and correspond to the segments and , respectively. Thus, decomposes into the four parts , and . This decomposition is shown in Figure 8(a).
Since is convex, if and only if all parts of are contained in . Note that and lie in , as both and are contained in . To prove , it remains to show that and are contained in .
Containment of in .
During the transition between and in the counterclockwise traversal on , it follows a simple path, denoted by , which lies outside . The path exits and re-enters through the endpoints of and .
Let and denote the vertices in corresponding to and , respectively. The link instruction is derived from the directed edge in . The direction of the edge is determined by how winds around (either clockwise or counterclockwise) and whether the path exits through the endpoint of or that of . If winds around counterclockwise, it exits from and re-enters at . Otherwise, it exits from and re-enters at . Figure 8(a) illustrates both cases.
Up to this point, we consider both clockwise- and counterclockwise-type instructions. However, counterclockwise ones can be omitted in the reconfiguration. Assume that winds around counterclockwise. By Corollary 7, there exists a unique component whose boundary contains , , and the path . Since is a weakly simple polygon, we can traverse in counterclockwise order. This traversal encounters a sequence of circular intervals in , and, from the construction of , each consecutive pair of intervals in this sequence corresponds to an edge in whose direction is determined by whether the subpath of between the intervals winds around clockwise or counterclockwise.
Since the traversal of follows the path from to that winds around counterclockwise, the other subpath of runs from back to , and winds around clockwise. This path encounters a sequence of intervals in starting from to , where each consecutive pair of intervals induces a clockwise-type edge in . In Figure 6(b), the counterclockwise-type path from to corresponds to the sequence of clockwise-type paths and . Thus, link instructions associated with counterclockwise-type edges can be omitted without affecting the resulting partition .
Without loss of generality, we restrict our analysis to clockwise type instructions. In this case, is a path from to . The path can be continuously deformed into a path on while preserving its endpoints. As illustrated in Figure 8(b), if intersects at a point , then must pass through . This implies that intersects itself at , contradicting that is a simple polygon.
Lemma 14.
All points on lie within the interior of .
Note that a point if and only if there exists a sufficiently small ball centered at such that . We slightly extend the polygonal chain beyond its endpoints and denote the resulting chain by for and . Since by Lemma 14, also lies in . Furthermore, as and are non-degenerate, the slight extension guarantees that .
Turning points on .
Without loss of generality, assume is a vertical strip, meaning that its boundary consists of two vertical lines. A portion of is a polygonal chain, consisting of a sequence of line segments. As we traverse a polygonal chain from one endpoint to the other, these line segments are encountered sequentially. A point is called a turning point of if the traversal changes its horizontal direction (from leftward to rightward or vice versa) at . Since and lie sufficiently close to and along , every turning must occur on .
When contains vertical edges, the above definition of turning points is not sufficient. Consider a path that initially moves in the positive (or negative) -direction, then follows a vertical segment, and subsequently moves in the negative (or positive) -direction. We define the lowest point on the vertical segment as the unique turning point on that segment. See Figure 9(a).
Note that the number of turning points is invariant under the traversal direction; that is, it remains unchanged whether we traverse from to or in the reverse direction. As illustrated in Figure 9(b), if there are two turning points on , we can draw a vertical guillotine cut in such that is disconnected, since all points on lie within . This implies that cannot be -convex with respect to .
Lemma 15.
If is -convex with respect to , then the number of turning points on is at most one.
Since both and lie in , . If there are no turning points on , then the points with the largest and smallest -coordinates along appear at and . Since is a vertical slab, all points on lie in .
Consider the case that has a turning point at , and it is unique by Lemma 15. Then, the point with the largest or smallest -coordinate along may appear at . Without loss of generality, we assume that is the point with the largest -coordinate. The point with the smallest -coordinate lies at or .
Recall that the path follows from to outside and is deformed into the path that traverses . Note that is a convex vertex of with locally largest -coordinate, and encloses from outside . It follows that must pass through a point with -coordinate at least . Since , the -coordinate of is smaller than that of the right boundary of . Thus, . See Figure 9(c).
Containment of within .
Revisiting the boundary of , we have shown that three parts, , and , are contained in . The remaining part is which is the portion of the inner -offset polygon of . By definition of the offset polygon, each edge of is parallel to its corresponding edge in and the edges of appear in the same cyclic order along its boundary as the edges of .
We traverse the chain from to . Let and be the edges of that contain the first and last segments of this chain, respectively. Likewise, traversing from to gives edges of incident to and , respectively. We claim that the edges of corresponding to and appear along the traversal of .
The segments and lie on edges of and , respectively. Since and , the edges of corresponding to and are incident to and , respectively. Recall that we work on the extended chain , obtained by slightly extending . This guarantees that the corresponding edges of appear along . Consequently, the sequence of line segments forming corresponds to a subsequence of those forming . See Figure 9(c) for an illustration of this correspondence. Thus, by Lemma 15, the number of turning points of is also at most one.
Assuming that the largest -coordinate of occurs at its turning point, the largest -coordinate of is smaller than that of . The argument is symmetric when the smallest -coordinate is attained at the turning point. It follows that is also contained in , which completes the proof that . Hence, the reconfigured partition is a solution to the problem with at most connected pieces; thus, by definition, .
6 Bang-type theorem for partitions of a convex body
We adapt the reconfiguration technique in Section 4 to prove Theorem 1. We then show that, when , an optimal partition of a convex polygon is achieved by equally spaced parallel cuts, which can be computed in linear time.
Let be a convex body in , and let be its arbitrary partition. Note that each is compact and possibly non-convex. Let denote a convex hull of a set in . A pocket of is defined as a closure of a connected component of . Each pocket is bounded by a subpath along and a unique line segment lying outside . We refer to this segment as the hull-edge of the pocket.
To convexify , we iteratively reallocate its pockets to . However, such a reallocation may split other pieces with . Accordingly, we perform a reconfiguration step to merge such fragments into a single piece in , ensuring that each piece remains connected.
This configuration mirrors Section 4, but with spatial roles reversed. Previously, we considered the restriction of a partition to a subpolygon , and reconnected the fragments of other pieces within . Here, we restrict the partition to the complement of a pocket, and consider the fragments of other pieces that lie outside the pocket. The circular intervals in the earlier setting now correspond to the intervals along the hull-edge of the pocket.
Lemma 16.
Let be a partition of a convex body . Then, there exists a convex partition , such that for all and .
By Lemma 16, we have a convex partition such that for all and . Given this convex partition, Akopyan [4] showed that , where . For any direction , we have . Thus, for any subset , .
Optimal partition for a convex polygon.
Let be a convex polygon with vertices, and let such that . Choose an arbitrary vector ; without loss of generality, assume that . Let be the leftmost vertex of , and partition by vertical lines along for all . This partitions into pieces, each of horizontal width at most 1, and it is a feasible solution to . Since is chosen arbitrarily, .
Suppose, for the sake of contradiction, that the optimal partition has fewer than pieces. Let be an optimal partition for , with . By Theorem 1, we have . Since each satisfies unit-width constraint , there exists such that . Thus, .
We analyze two cases depending on whether attains a minimum over . If it does, we have , and . As is an integer, . If no minimum is attained over , and . Then . Both cases contradict our assumption, and thus .
Let be a vector minimizing , computed in time for [18]. Assume that is given. For the vertices of given in counterclockwise order, such parallel cuts can be computed in time [12]. Since for all , . For fixed , starts at when and increases monotonically, approaching as .
Corollary 17.
Let be a convex polygon with vertices, and let be sets of unit vectors such that . Then an optimal partition for the problem is achieved by equally spaced parallel cuts orthogonal to that minimizes . Given such a direction , the partition can be computed in time.
Remarks.
We work in the Real RAM model, which supports unit-cost arithmetic () and comparisons on real numbers. Our algorithms perform integer rounding via comparisons.
References
- [1] Mikkel Abrahamsen and Nichlas Langhoff Rasmussen. Partitioning a polygon into small pieces. In Proc. 2025 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). Society for Industrial and Applied Mathematics, 2025.
- [2] Mikkel Abrahamsen and Jack Stade. Hardness of packing, covering and partitioning simple polygons with unit squares. In Proc. 65th IEEE Symposium on Foundations of Computer Science (FOCS). IEEE, 2024. doi:10.1109/FOCS61266.2024.00087.
- [3] Arseniy Akopyan and Roman Karasev. Kadets-type theorems for partitions of a convex body. Discrete & Computational Geometry, 48:766–776, 2012. doi:10.1007/S00454-012-9437-1.
- [4] Arseniy Akopyan, Roman Karasev, and Fedor Petrov. Bang’s problem and symplectic invariants. Journal of Symplectic Geometry, 17(6):1579–1611, 2019.
- [5] Ralph Alexander. A problem about lines and ovals. The American Mathematical Monthly, 75(5):482–487, 1968.
- [6] Keith Ball. The plank problem for symmetric bodies. Inventiones Mathematicae, 104:535–543, 1991.
- [7] Thøger Bang. A solution of the “plank problem”. Proc. American Mathematical Society, 2(6):990–993, 1951.
- [8] Jørgen Bang-Jensen and Gregory Z. Gutin. Digraphs: Theory, Algorithms and Applications. Springer Science & Business Media, 2008.
- [9] Andras Bezdek and Károly Bezdek. Conway’s fried potato problem revisited. Archiv der Mathematik, 66(6):522–528, 1996.
- [10] Károly Bezdek. Plank theorems via successive inradii. In Discrete Geometry and Algebraic Combinatorics, Contemporary Mathematics, volume 625, pages 1–8. American Mathematical Society, 2013. URL: http://www.ams.org/books/conm/625/12489.
- [11] Maike Buchin and Leonie Selbach. Decomposing polygons into fat components. In Proc. 33rd Canadian Conference on Computational Geometry (CCCG), pages 175–184, 2021.
- [12] Jaehoon Chung, Sang Won Bae, Chan-Su Shin, Sang Duk Yoon, and Hee-Kap Ahn. Approximating convex polygons by histogons. In Proc. 34th Canadian Conference on Computational Geometry (CCCG), 2022.
- [13] Mirela Damian. Exact and approximation algorithms for computing optimal fat decompositions. Computational Geometry: Theory and Applications, 28(1):19–27, 2004. doi:10.1016/J.COMGEO.2004.01.004.
- [14] Mirela Damian and Sriram V. Pemmaraju. Computing optimal diameter-bounded polygon partitions. Algorithmica, 40(1):1–14, 2004. doi:10.1007/S00453-004-1092-3.
- [15] Mirela Damian-Iordache. Shape constrained polygon decomposition and graph domination problems. PhD thesis, University of Iowa, Iowa City, IA 52242, 2000.
- [16] Richard John Gardner. Relative width measures and the plank problem. Pacific Journal of Mathematics, 135(2):299–312, 1988.
- [17] J. W. S. Hearle. The structural mechanics of fibers. Journal of Polymer Science Part C: Polymer Symposia, 20:215–230, 1967.
- [18] Michael B. Houle and Godfried T. Toussaint. Computing the width of a set. In Proc. 1st Annual Symposium on Computational Geometry (SCG), pages 1–7, 1985.
- [19] Henry F. Hunter. Some special cases of bang’s inequality. Proc. American Mathematical Society, 117(3):819–821, 1993.
- [20] Joseph O’Rourke and Geetika Tewari. The structure of optimal partitions of orthogonal polygons into fat rectangles. Computational Geometry, 28(1):49–71, 2004. doi:10.1016/J.COMGEO.2004.01.007.
- [21] Gregory J. E. Rawlins. Explorations in restricted orientation geometry. PhD thesis, Indiana University, Department of Computer Science, Bloomington, 1987.
- [22] Chris Worman. Decomposing polygons into bounded diameter components. In Proceedings of the 15th Canadian Conference on Computational Geometry (CCCG), pages 103–107, 2003.
