Local search heuristics for single-machine scheduling with batching to minimize the number of late jobs |
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| Institution: | 1. Department of Industrial and Management Systems Engineering, Kuwait University, P.O. Box 5969, Safat, Kuwait;1. Instituto Superior de Economia e Gestão, Universidade de Lisboa, Rua do Quelhas 6, 1200-781 Lisboa, Portugal;2. ISCTE-IUL – Instituto Universitário de Lisboa, Av. das Forças Armadas, 1649-026 Lisboa, Portugal;3. CMAF-CIO, Universidade de Lisboa, 1749-016 Lisboa, Portugal |
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| Abstract: | Local search heuristics are developed for a problem of scheduling jobs on a single machine. Jobs are partitioned into families, and a set-up time is necessary when there is a switch in processing jobs from one family to jobs of another family. The objective is to minimize the number of late jobs. Four alternative local search methods are proposed: multi-start descent, simulated annealing, tabu search and a genetic algorithm. The performance of these heuristics is evaluated on a large set of test problems. The best results are obtained with the genetic algorithm; multi-start descent also performs quite well. |
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