Comparing an ACO algorithm with other heuristics for the single machine scheduling problem with sequence-dependent setup times
We compare several heuristics for solving a single machine scheduling problem. In the operating situation modelled, setup times are sequence-dependent and the objective is to minimize total tardiness. We describe an Ant Colony Optimization (ACO) algorithm having a new feature using look-ahead inform...
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| Published in | The Journal of the Operational Research Society Vol. 53; no. 8; pp. 895 - 906 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Taylor & Francis
01.08.2002
Palgrave Macmillan Press Palgrave Macmillan UK Palgrave Taylor & Francis Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0160-5682 1476-9360 |
| DOI | 10.1057/palgrave.jors.2601390 |
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| Abstract | We compare several heuristics for solving a single machine scheduling problem. In the operating situation modelled, setup times are sequence-dependent and the objective is to minimize total tardiness. We describe an Ant Colony Optimization (ACO) algorithm having a new feature using look-ahead information in the transition rule. This feature shows an improvement in performance. A comparison with a genetic algorithm, a simulated annealing approach, a local search method and a branch-and-bound algorithm indicates that the ACO that we describe is competitive and has a certain advantage for larger problems. |
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| AbstractList | We compare several heuristics for solving a single machine scheduling problem. In the operating situation modelled, setup times are sequence-dependent and the objective is to minimize total tardiness. We describe an Ant Colony Optimization (ACO) algorithm having a new feature using look-ahead information in the transition rule. This feature shows an improvement in performance. A comparison with a genetic algorithm, a simulated annealing approach, a local search method and a branch-and-bound algorithm indicates that the ACO that we describe is competitive and has a certain advantage for larger problems. Journal of the Operational Research Society. Several heuristics for solving a single machine scheduling problem are compared. In the operating situation modeled, setup times are sequence-dependent and the objective is to minimize total tardiness. An Ant Colony Optimization (ACO) algorithm having a new feature using look-ahead information in the transition rule is described. This feature shows an improvement in performance. A comparison with a genetic algorithm, a simulated annealing approach, a local search method and a branch-and-bound algorithm indicates that the ACO that is described is competitive and has a certain advantage for larger problems. We compare several heuristics for solving a single machine scheduling problem. In the operating situation modelled, setup times are sequence-dependent and the objective is to minimize total tardiness. We describe an Ant Colony Optimization (ACO) algorithm having a new feature using look-ahead information in the transition rule. This feature shows an improvement in performance. A comparison with a genetic algorithm, a simulated annealing approach, a local search method and a branch-and-bound algorithm indicates that the ACO that we describe is competitive and has a certain advantage for larger problems. |
| Author | Price, W L Gravel, M Gagné, C |
| Author_xml | – sequence: 1 givenname: C surname: Gagné fullname: Gagné, C organization: Université du Québec, Chicoutimi – sequence: 2 givenname: W L surname: Price fullname: Price, W L email: wilson.price@fsa.ulaval.ca organization: Université Laval – sequence: 3 givenname: M surname: Gravel fullname: Gravel, M organization: Université du Québec, Chicoutimi |
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| Keywords | scheduling metaheuristic sequence-dependent setups ant colony optimization total tardiness single machine Setup time Scheduling Single machine NP hard problem |
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| Snippet | We compare several heuristics for solving a single machine scheduling problem. In the operating situation modelled, setup times are sequence-dependent and the... Several heuristics for solving a single machine scheduling problem are compared. In the operating situation modeled, setup times are sequence-dependent and the... |
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| SubjectTerms | Algorithms ant colony optimization Ants Applied sciences Business and Management Exact sciences and technology Genetic algorithms Heuristic Heuristics Insect colonies Insect genetics Job shops Lateness Management metaheuristic Operational research and scientific management Operational research. Management science Operations research Operations Research/Decision Theory Optimization Pheromones Scheduling Scheduling, sequencing sequence-dependent setups single machine Studies Theoretical Paper Theoretical Papers total tardiness |
| Title | Comparing an ACO algorithm with other heuristics for the single machine scheduling problem with sequence-dependent setup times |
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