Dosdogru, A.T.Geyik, F.Göçken, M.2025-01-062025-01-0620142-s2.0-84923873783https://hdl.handle.net/20.500.14669/1409Computer and Industrial Engineering; et al.; Gaziantep University; Istanbul Commercial University; Journal of Intelligent Manufacturing Systems; Sakarya University, Department of Industrial EngineeringJoint International Symposium on "The Social Impacts of Developments in Information, Manufacturing and Service Systems" 44th International Conference on Computers and Industrial Engineering, CIE 2014 and 9th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2014 -- 14 October 2014 through 16 October 2014 -- Istanbul -- 110500This paper handles representation types of genetic algorithm for a two-stage supply chain distribution problem. In this respect, three representation types are selected, namely priority-based, permutation and matrix representation. Genetic algorithm is designed for all representation types by considering a two-stage supply chain distribution problem. The objective function is selected as total distribution cost with fixed charges. Twenty problems are selected from literature to compare representation types. Each problem is solved by using genetic algorithms considering representation types and performances of algorithms are compared. Computational results showed that priority-based representation and permutation representation are more efficient than the matrix representation in terms of computational times.eninfo:eu-repo/semantics/closedAccessGenetic algorithmRepresentationTwo-stage supply chain distribution problemConference Object394383