A filtering algorithm for global sequencing constraints

Régin, Jean‐Charles; Puget, Jean‐François

doi:10.1007/bfb0017428

Cited by 74 publications

(69 citation statements)

References 3 publications

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“…A solution of the decision variant of the car sequencing problem (considered in this paper) is to find an assignment of cars to the slot that satisfies both the demand and the capacity constraints, which is NP-complete [11]. It was studied in many works [15,17,28,30] and an optimization variant was considered in the 2005 ROADEF challenge [31]. To model this problem, we consider n class variables (one for each car), the domain of these variables is the set of car classes.…”

Section: Car Sequencing Problemsmentioning

confidence: 99%

“…To model this problem, we consider n class variables (one for each car), the domain of these variables is the set of car classes. We do not use any global constraint propagation among those proposed in [17] or in [28], but just FC propagation.…”

Section: Car Sequencing Problemsmentioning

confidence: 99%

“…[17]), 37 instances are solved using GSC and 39 using GSC combined with regular (with a timeout of 3600 seconds). In this paper, the ordering heuristics used are the best between dom and the slack heuristic proposed in [28]. With the proposed heuristic based on Wvar⊕Lexico, with just FC propagation, the best tree search method (Non-binary LDS) is clearly very well performing since it solved 65 instances.…”

Section: Car Sequencing Problemsmentioning

confidence: 99%

See 2 more Smart Citations

Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems

Huguet¹,

López²,

Karoui³

2012

J Math Model Algor

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In this paper, we propose mechanisms to improve instantiation heuristics by incorporating weighted factors on variables. The proposed weight-based heuristics are evaluated on several tree search methods such as chronological backtracking and discrepancy-based search for both constraint satisfaction and optimization problems. Experiments are carried out on random constraint satisfaction problems, car sequencing problems, and jobshop scheduling with time-lags, considering various parameter settings and variants of the methods. The results show that weighting mechanisms reduce the tree size and then speed up the solving time, especially for the discrepancy-based search method.

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Section: Car Sequencing Problemsmentioning

confidence: 99%

Section: Car Sequencing Problemsmentioning

confidence: 99%

Section: Car Sequencing Problemsmentioning

confidence: 99%

See 1 more Smart Citation

Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems

Huguet¹,

López²,

Karoui³

2012

J Math Model Algor

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show abstract

“…Régin [20] relies on the sequencing constraint [21] to propagate the "interdistance constraint". However, we believe it is somewhat easier to consider this constraint as a pure scheduling constraint.…”

Section: Inter-distance Constraint Vs Scheduling Constraintsmentioning

confidence: 99%

Inter-distance Constraint: An Extension of the All-Different Constraint for Scheduling Equal Length Jobs

Artiouchine

Baptiste

2005

Principles and Practice of Constraint Programming - CP 2005

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Abstract. We study a global constraint, the "inter-distance constraint" that ensures that the distance between any pair of variables is at least equal to a given value. When this value is 1, the inter-distance constraint reduces to the all-different constraint. We introduce an algorithm to propagate this constraint and we show that, when domains of the variables are intervals, our algorithm achieves arc-B-consistency. It provides tighter bounds than generic scheduling constraint propagation algorithms (like edge-finding) that could be used to capture this constraint. The worst case complexity of the algorithm is cubic but it behaves well in practice and it drastically reduces the search space. Experiments on special Job-Shop problems and on an industrial problem are reported.

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“…A filtering algorithm is described in (Régin and Puget, 1997). Thanks to it, some problems of the CSP-Lib have been closed.…”

Section: Definition 13 a Global Sequencing Constraint Is A Constraintmentioning

confidence: 99%

Global Constraints and Filtering Algorithms

Régin¹

2004

Constraint and Integer Programming

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Constraint programming (CP) is mainly based on filtering algorithms; their association with global constraints is one of the main strengths of CP. This chapter is an overview of these two techniques. Some of the most frequently used global constraints are presented. In addition, the filtering algorithms establishing arc consistency for two useful constraints, the alldiff and the global cardinality constraints, are fully detailed. Filtering algorithms are also considered from a theoretical point of view: three different ways to design filtering algorithms are described and the quality of the filtering algorithms studied so far is discussed. A categorization is then proposed. Over-constrained problems are also mentioned and global soft constraints are introduced.

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A filtering algorithm for global sequencing constraints

Cited by 74 publications

References 3 publications

Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems

Weight-based Heuristics for Constraint Satisfaction and Combinatorial Optimization Problems

Inter-distance Constraint: An Extension of the All-Different Constraint for Scheduling Equal Length Jobs

Global Constraints and Filtering Algorithms

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