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Documents authored by Le, Duc Anh

Document
DOI: 10.4230/LIPIcs.CP.2025.25
Aircraft Resource-Constrained Assembly Line Balancing with Learning Effect: A Constraint Programming Approach

Authors: Duc Anh Le, Stéphanie Roussel, and Christophe Lecoutre

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
Balancing aeronautical assembly lines is a major challenge in modern aerospace manufacturing. Aircraft manufacturing plants typically have a predetermined production rate, but the production system requires a period of adaptation at start-up. This phenomenon, known as the learning effect, refers to the gradual improvement in efficiency through task repetition, thereby reducing task duration. However, the stability of an assembly line is also a critical factor, as any change in the production process incurs costs. In this study, Constraint Programming (CP) is used to optimise assembly line balancing, taking into account the learning effect to address the trade-off between achieving target production rates and minimising adjustments to the line.
Cite as

Duc Anh Le, Stéphanie Roussel, and Christophe Lecoutre. Aircraft Resource-Constrained Assembly Line Balancing with Learning Effect: A Constraint Programming Approach. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 25:1-25:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{le_et_al:LIPIcs.CP.2025.25,
  author =	{Le, Duc Anh and Roussel, St\'{e}phanie and Lecoutre, Christophe},
  title =	{{Aircraft Resource-Constrained Assembly Line Balancing with Learning Effect: A Constraint Programming Approach}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{25:1--25:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.25},
  URN =		{urn:nbn:de:0030-drops-238863},
  doi =		{10.4230/LIPIcs.CP.2025.25},
  annote =	{Keywords: Assembly Line Balancing, Resource-Constrained, Learning Effect, Ramp-Up, Aeronautic, Constraint Programming, Dominance-Breaking}
}
Document
DOI: 10.4230/LIPIcs.CP.2024.18
Learning Effect and Compound Activities in High Multiplicity RCPSP: Application to Satellite Production

Authors: Duc Anh Le, Stéphanie Roussel, Christophe Lecoutre, and Anouck Chan

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
This paper addresses the High Multiplicity Resource-Constrained Project Scheduling Problem (HM-RCPSP), in which multiple projects are performed iteratively while sharing limited resources. We extend this problem by integrating the learning effect, which makes the duration of some activities decrease when they are repeated. Learning effect can be represented by any decreasing function, allowing us to get flexibility in modeling various scenarios. Additionally, we take composition of activities into consideration for reasoning about precedence and resources in a more abstract way. A Constraint Programming model is proposed for this richer problem, including a symmetry-breaking technique applied to some activities. We also present a heuristic-based search strategy. The effectiveness of these solving approaches is evaluated through an experimentation conducted on data concerning real-world satellite assembly lines, as well as on some adapted literature benchmarks. Obtained results demonstrate that our methods serve as robust baselines for addressing this novel problem (denoted by HM-RCPSP/L-C).
Cite as

Duc Anh Le, Stéphanie Roussel, Christophe Lecoutre, and Anouck Chan. Learning Effect and Compound Activities in High Multiplicity RCPSP: Application to Satellite Production. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 18:1-18:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{le_et_al:LIPIcs.CP.2024.18,
  author =	{Le, Duc Anh and Roussel, St\'{e}phanie and Lecoutre, Christophe and Chan, Anouck},
  title =	{{Learning Effect and Compound Activities in High Multiplicity RCPSP: Application to Satellite Production}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{18:1--18:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.18},
  URN =		{urn:nbn:de:0030-drops-207037},
  doi =		{10.4230/LIPIcs.CP.2024.18},
  annote =	{Keywords: High-multiplicity Project Scheduling, Learning Effect, Compound Activities, Satellite Assembly Line, Constraint Programming, Symmetry Breaking}
}
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