A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Computers and Operations Research
A genetic alorithm for multiple objective sequencing problems in mixed model assembly lines
Computers and Operations Research
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
How to Solve It: Modern Heuristics
How to Solve It: Modern Heuristics
Applying adaptive algorithms to epistatic domains
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
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The aim of this paper is to study the problem of sequencing a set of vehicles within an industrial environment considering the assembly shop objectives, but also the objectives of the paint shop. The first approach is to solve the problem with a mono-objective function. One heuristic (a progressive, construction-sequence algorithm) and three meta-heuristics (simulated annealing, variable neighbourhood search and an evolutionary algorithm) are described and compared. As the mono-objective approach has limited possibilities, a multi-objective heuristic is finally presented and tested. Because of the industrial context of this research, the computation time is a decisive factor to select the appropriate heuristic.