Ant colony optimization for multi-objective flow shop scheduling problem
| Autor: | Mehmet Mutlu Yenisey, Betul Yagmahan |
|---|---|
| Přispěvatelé: | Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü., Yağmahan, Betül, J-2416-2015 |
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: |
Rate-monotonic scheduling
Earliest deadline first scheduling System Optimization Mathematical optimization General Computer Science Computer science Scheduling (production processes) Dynamic priority scheduling Fair-share scheduling Scheduling (computing) Ant colony optimization M-machine Fixed-priority pre-emptive scheduling Engineering Nurse scheduling problem Lottery scheduling Flow shop N-job Problem solving Flow Shop Scheduling Permutation Flowshop No-Wait Multi-objective Computer science interdisciplinary applications Job shop scheduling Scheduling Ant colony optimization algorithms General Engineering Search Flow shop scheduling Round-robin scheduling Algorithm Computational efficiency Engineering industrial Heuristics Algorithms |
| Popis: | Flow shop scheduling problem consists of scheduling given jobs with same order at all machines. The job can be processed on at most one machine; meanwhile one machine can process at most one job. The most common objective for this problem is makespan. However, multi-objective approach for scheduling to reduce the total scheduling cost is important. Hence, in this study, we consider the flow shop scheduling problem with multi-objectives of makespan, total flow time and total machine idle time. Ant colony optimization (ACO) algorithm is proposed to solve this problem which is known as NP-hard type. The proposed algorithm is compared with solution performance obtained by the existing multi-objective heuristics. As a result, computational results show that proposed algorithm is more effective and better than other methods compared. |
| Databáze: | OpenAIRE |
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