An integer linear programming approach and a hybrid variable neighborhood search for the car sequencing problem

Prandtstetter, Matthias; Raidl, Günther R.

doi:10.1016/j.ejor.2007.04.044

Cited by 72 publications

(39 citation statements)

References 8 publications

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“…Such hybrid approaches are believed to benefit from synergetic exploitation of complementary strength of their components. Indeed, many works concerning non-trivial optimization problems report that hybrids are more efficient and flexible than traditional metaheuristics applied separately (Prandtstetter and Raidl 2008;Burke et al 2010;Hu et al 2008;Cambazard et al 2012). In this work we confirm these observations.…”

Section: Discussionsupporting

confidence: 81%

A hybrid MIP-based large neighborhood search heuristic for solving the machine reassignment problem

2015

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We present a hybrid metaheuristic approach for the machine reassignment problem, which was proposed for ROADEF/EURO Challenge 2012. The problem is a combinatorial optimization problem, which can be viewed as a highly constrained version of the multidimensional bin packing problem. Our algorithm, which took the third place in the challenge, consists of two components: a fast greedy hill climber and a large neighborhood search, which uses mixed integer programming to solve subproblems. We show that the hill climber, although simple, is an indispensable component that allows us to achieve high quality results especially for large instances of the problem. In the experimental part we analyze two subproblem selection methods used by the large neighborhood search algorithm and compare our approach with the two best entries in the competition, observing that none of the three algorithms dominates others on all available instances.

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Section: Discussionsupporting

confidence: 81%

A hybrid MIP-based large neighborhood search heuristic for solving the machine reassignment problem

2015

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“…Les travaux de toutes les équipes n'ayant pas été publiés, rénumération précédente n'est donc pas exhaustive. À la suite du challenge, d'autres auteurs ont abordé ce problème en utilisant la programmation linéaire en nombres entiers Gagné et al 2006;Prandtstetter et Raidi 2007] [Osman et Laporte 1996]. Parmi les métaheuristiques les plus utilisées, citons le recuit simulé [Kirkpatrick et al 1983], la recherche avec tabous [Glover 1986], l'optimisation par colonie de fourmis [Dorigo 1992] et bien entendu les algorithmes génétiques [Holland 1975] qui font partie de la famille des algorithmes évolutionnaires dont les principes de base sont brièvement décrits à la section suivante.…”

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Algorithmes évolutionnaires pour l'ordonnancement industriel :

Zinflou¹

2008

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“…Computational results show that their approach obtained excellent performance. A similar approach of searching large neighborhoods by a MIP solver is applied by Prandtstetter and Raidl to a car sequencing problem [94]. PNSP methods have been successfully applied in combination with constraint programming techniques.…”

Section: Other Approachesmentioning

confidence: 99%

Usage of Exact Algorithms to Enhance Stochastic Local Search Algorithms

Dumitrescu

Stützle

2009

Matheuristics

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Exact mathematical programming techniques such as branch-andbound or dynamic programming and stochastic local search techniques have traditionally been seen as being two general but distinct approaches for the effective solution of combinatorial optimization problems, each having particular advantages and disadvantages. In several research efforts true hybrid algorithms, which exploit ideas from both fields, have been proposed. In this chapter we review some of the main ideas of several such combinations and illustrate them with examples from the literature. Our focus here is on algorithms that have the main framework given by the local search and use exact algorithms to solve subproblems.

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An integer linear programming approach and a hybrid variable neighborhood search for the car sequencing problem

Cited by 72 publications

References 8 publications

A hybrid MIP-based large neighborhood search heuristic for solving the machine reassignment problem

A hybrid MIP-based large neighborhood search heuristic for solving the machine reassignment problem

Algorithmes évolutionnaires pour l'ordonnancement industriel :

Usage of Exact Algorithms to Enhance Stochastic Local Search Algorithms

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