Onder BulutM. Fatih TasgetirenM. Murat FadilogluTasgetiren, M. FatihBulut, OnderFadiloglu, M. MuratD HuangY GanP GuptaMM Gromiha2025-10-062012978-3-642-25943-297836422594320302-974310.1007/978-3-642-25944-9_82-s2.0-84855665274https://gcris.yasar.edu.tr/handle/123456789/6860https://doi.org/10.1007/978-3-642-25944-9_8In 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.Englishinfo:eu-repo/semantics/closedAccessEconomic lot scheduling problem, extended basic period, power-of-two policy, genetic algorithm, variable neighborhood searchGenetic AlgorithmVariable Neighborhood SearchEconomic Lot Scheduling ProblemPower-of-Two PolicyExtended Basic PeriodConference Object