An Efficient Heuristic Algorithm for Capacitated Lot Sizing Problem with Overtime Decisions
| Autor: | Mehmet Mutlu Yenisey, Cagatay Iris |
|---|---|
| Přispěvatelé: | Department of Industrial Engineering Maçka, Istanbul Technical University (ITÜ), Jan Frick, Bjørge Timenes Laugen, TC 5, WG 5.7 |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization 021103 operations research Heuristic (computer science) Computer science 0211 other engineering and technologies Lot Sizing with Overtime Decisions 02 engineering and technology Sizing 020901 industrial engineering & automation Master production schedule Production planning Robustness (computer science) Simulated annealing Dynamic demand Production Planning [INFO]Computer Science [cs] Simulated Annealing Time complexity Global Search |
| Zdroj: | IFIP Advances in Information and Communication Technology International Conference on Advances in Production Management Systems (APMS) International Conference on Advances in Production Management Systems (APMS), Sep 2011, Stavanger, Norway. pp.107-114, ⟨10.1007/978-3-642-33980-6_13⟩ Advances in Production Management Systems. Value Networks: Innovation, Technologies, and Management ISBN: 9783642339790 APMS |
| DOI: | 10.1007/978-3-642-33980-6_13⟩ |
| Popis: | Part 1: Production Process; International audience; Capacitated Lot Sizing Problem is a very important tactical level decision making problem that answers the questions of producing when and how many in dynamic demand environment. Solving Capacitated Lot Sizing Problem with Overtime decisions (CLSPO) and extensions derived from the fundamental structure optimally suffer from combinatorial nature of the problem. The aim of the study is to form a two-stage heuristic algorithm to solve related problem in polynomial time. In first part, characteristics of problem structure are presented. Dominance properties are presented to help algorithm obtain a bounded search area. Proposed algorithm directly utilizes such shortcoming. Performance of approach is tested by using different criteria. And finally, robustness test are applied to check how well algorithm performs against fluctuations in its data. Simulated annealing as improvement heuristic performs well for related problem. It is also observed that fluctuations of data directly affects performance outcome. Obtained results also reveal that performance of improvement heuristic highly depends on constructive heuristic. Algorithm is also applied to an industry case study to plan master production schedule with minimum costs. |
| Databáze: | OpenAIRE |
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