Solving Car Sequencing Problems by Local Optimization

Authors:
Markus Puchta;Jens Gottlieb
Affiliations:
-;-
Venue:
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Year:
2002

Citing 2
Cited 2

Threshold accepting: a general purpose optimization algorithm appearing superior to simulated annealing

Journal of Computational Physics
Local Search in Combinatorial Optimization

Local Search in Combinatorial Optimization

A GRASP approach for the extended car sequencing problem

Journal of Scheduling
A study of greedy, local search, and ant colony optimization approaches for car sequencing problems

EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing

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Abstract

Real-world car sequencingproblems deal with lots of constraints, which differ in their types and priorities. We evaluate three permutation-based local search algorithms that use different acceptance criteria for moves. The algorithms meet industrial requirements to obtain acceptable solutions in a rather short time. It is essential to employ move operators which can be evaluated quite fast. Further, usingdifferen t move types enlarges the neighbourhood, thereby decreasing the total number of local optima in the search space. The comparison of the acceptance criteria shows that the greedy approach is inferior to two variants of threshold acceptingthat allow escapingfrom local optima.