Journal Article10.1023/A:1013653332557
Mathematical Programming Techniques in Constraint Programming: A Short Overview
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TL;DR: This paper briefly presents the integration directions explored in the literature, and provides some pointers to relevant work in these directions.
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Abstract: In recent years, the integration of techniques from Artificial Intelligence and Operations Research has shown to improve the solutions of complex and large scale combinatorial optimization problems, in terms of efficiency, scalability and optimality. In this context, Constraint Programming is an emerging discipline situated at the confluence of the two fields that has been recognized as a suitable environment for achieving such an integration. This paper briefly presents the integration directions explored in the literature, and provides some pointers to relevant work in these directions.
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Citations
Analysis of a parallel machine scheduling problem with sequence dependent setup times and job availability intervals
TL;DR: The initial investigations show that the pure CP model is very efficient in obtaining good quality feasible solutions but, fails to report the optimal solution for the majority of the problem instances, while the two logic-based Benders decomposition algorithms are able to obtain near optimal solutions.
61
Constraint programming approaches to disassembly line balancing problem with sequencing decisions
TL;DR: This study is the first that uses constraint programming (CP) for the disassembly line balancing problems, and shows that the proposed CP-based solution approach produces excellent results in all large test instances by either improving the best solutions (found so far) or establishing new benchmark solutions.
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Submodularity and its application to some global constraints
D. Magos,I. Mourtos +1 more
TL;DR: The cumulative constraint, when all tasks are identical, has the submodular/supermodular representation property, which means that the system of any two constraints not necessarily of the same type, each bearing the above-mentioned property, has an integral relaxation given by the conjunction of the linear inequalities representing each individual constraint.
3
Crop planting layout optimization in sustainable agriculture: A constraint programming approach
Tommaso Adamo,Lucio Colizzi,Giovanni Dimauro,Emanuela Guerriero,Deborah Pareo +4 more
2
References
Greedy Randomized Adaptive Search Procedures
TL;DR: This paper defines the various components comprising a GRASP and demonstrates, step by step, how to develop such heuristics for combinatorial optimization problems.
Using Constraint Programming and Local Search Methods to Solve Vehicle Routing Problems
Paul Shaw
- 26 Oct 1998
TL;DR: In this paper, a local search method called Large Neighbourhood Search (LNS) is used to solve vehicle routing problems, analogous to the shuffling technique of job shop scheduling.
1.4K
•Journal Article
Using constraint programming and local Search methods to solve vehicle routing problems
TL;DR: This work uses a local search method that is analogous to the shuffling technique of job-shop scheduling, and so meshes well with constraint programming technology, to solve vehicle routing problems.
1.4K
An algorithm for solving the job-shop problem
Jacques Carlier,Eric Pinson +1 more
TL;DR: In this paper, a branch and bound method for solving the job-shop problem is proposed, which is based on one-machine scheduling problems and is made more efficient by several propositions which limit the search tree by using immediate selections.
896
•Proceedings Article
A filtering algorithm for constraints of difference in CSPs
Jean-Charles Régin
- 01 Aug 1994
TL;DR: A new filtering algorithm is presented that achieves the generalized arc-consistency condition for these non-binary constraints and has been successfully used in the system RESYN, to solve the subgraph isomorphism problem.
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