European journal of operational research, 2005-11, Vol.167 (1), p.77-95
2005
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- Autor(en) / Beteiligte
- Titel
- A hybrid genetic algorithm for the job shop scheduling problem
- Ist Teil von
- European journal of operational research, 2005-11, Vol.167 (1), p.77-95
- Ort / Verlag
- Amsterdam: Elsevier B.V
- Erscheinungsjahr
- 2005
- Quelle
- Access via ScienceDirect (Elsevier)
- Beschreibungen/Notizen
- This paper presents a hybrid genetic algorithm for the job shop scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 0377-2217eISSN: 1872-6860DOI: 10.1016/j.ejor.2004.03.012Titel-ID: cdi_proquest_journals_204128509
- Format
- –
- Schlagworte
- Applied sciences, Exact sciences and technology, Genetic algorithm, Genetic algorithms, Heuristics, Job shop, Job shops, Operational research and scientific management, Operational research. Management science, Operations research, Production scheduling, Random keys, Scheduling, Scheduling, sequencing, Studies