Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
A genetic algorithm for flowshop sequencing
Computers and Operations Research - Special issue on genetic algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Complete Local Search with Memory
Journal of Heuristics
A very fast Tabu search algorithm for the permutation flow shop problem with makespan criterion
Computers and Operations Research
A computational study of the permutation flow shop problem based on a tight lower bound
Computers and Operations Research
An enhanced timetabling procedure for the no-wait job shop problem: a complete local search approach
Computers and Operations Research
Computers and Operations Research
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In this paper, we propose an algorithm named BDS (Bound-Driven Search) that combines features of exact and approximate methods. The proposed procedure may be seen as a local search algorithm that systematically explores (in a branch-and bound sense) the most promising nodes, thus preventing solutions from being reevaluated. Additionally, it can be regarded as an exact method as it may be able to guarantee that the solution found is optimal. We present the application of this new algorithm to a specific problem domain: the permutation flow shop scheduling problem with makespan objective. The subsequent computational experiments are encouraging, as the algorithm is able to yield exact or near exact solutions to most instances of the problem. Furthermore, the algorithm outperforms one of the best state-of-the-art algorithms for the problem.