A genetic algorithm for the economic lot scheduling problem under extended basic period approach and power-of-two policy

Authors:
Onder Bulut;M. Fatih Tasgetiren;M. Murat Fadiloglu
Affiliations:
Industrial Engineering Department, Yasar University, Izmir, Turkey;Industrial Engineering Department, Yasar University, Izmir, Turkey;Industrial and Systems Engineering Department, Izmir Economy University, Izmir, Turkey
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

In this study, we propose a genetic algorithm (GA) for the economic lot scheduling problem (ELSP) under extended basic period (EBP) approach and power-of-two (PoT) policy. The proposed GA employs a multi-chromosome solution representation to encode PoT multipliers and the production positions separately. Both feasible and infeasible solutions are maintained in the population through the use of some sophisticated constraint handling methods. Furthermore, a variable neighborhood search (VNS) algorithm is also fused into GA to further enhance the solution quality. The experimental results show that the proposed GA is very competitive to the best performing algorithms from the existing literature under the EBP and PoT policy.