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Constraint Solving and Particle Swarm Optimization for Fixture Layout Optimization

Authors Anna Vitali , Roberto Amadini , Vittorio Maniezzo , Maurizio Gabbrielli

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Subject Classification

ACM Subject Classification
  • Theory of computation → Constraint and logic programming
Keywords
  • Constraint Programming
  • Mixed-Integer Programming
  • Particle Swarm Optimization
  • Fixture Layout Optimization
  • Industrial Application

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Abstract

In the wood industry, ensuring the stability and immobility of a workpiece during machining is essential. Vacuum suction cups are commonly used as fixtures, as they can rotate to better conform to the workpiece perimeter. However, this rotational capability introduces additional complexity into fixture placement. This paper addresses the problem of optimally positioning rotatable fixtures by combining two complementary techniques. First, we solve a restricted version of the problem that neglects rotations using a constraint solver, yielding an initial feasible solution. This solution is then refined using a Particle Swarm Optimization algorithm that accounts for rotation. Experimental results show that the quality of the initial solution significantly influences the final placement, and that the proposed approach can effectively support expert operators in making improved decisions.

Cite As Get BibTex

Anna Vitali, Roberto Amadini, Vittorio Maniezzo, and Maurizio Gabbrielli. Constraint Solving and Particle Swarm Optimization for Fixture Layout Optimization. In 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 379, pp. 56:1-56:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.CP.2026.56

Author Details

Anna Vitali
  • Alma Mater Studiorum University of Bologna, Italy
Roberto Amadini
  • Alma Mater Studiorum University of Bologna, Italy
Vittorio Maniezzo
  • Alma Mater Studiorum University of Bologna, Italy
Maurizio Gabbrielli
  • Alma Mater Studiorum University of Bologna, Italy

Funding

This work is supported by PNRR - M4C2 - Investimenti 1.3, 3.3 e 3.4.

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