Integrating MILP and MCDM for Smart Warehouse Location Selection in Agricultural E-Commerce

dc.contributor.authorSholeh, M. B.
dc.contributor.authorRochim, A. F.
dc.contributor.authorNugraheni, D. M. K.
dc.date.accessioned2025-11-17T10:05:53Z
dc.date.issued2025
dc.description.abstractOptimizing warehouse locations is critical for reducing logistics costs, improving delivery reliability, and enhancing sustainability in agricultural e-commerce. This study applies Mixed-Integer Linear Programming (MILP) to filter optimal warehouse alternatives, followed by MARCOS for ranking. The findings indicate that MILP significantly impacts the selection process, with G7, G1, and G6 emerging as the top choices. Sensitivity analysis and comparisons with other MCDM methods confirm the robustness of the results. This research offers practical insights for improving supply chain efficiency and contributes to decision-making models for warehouse location optimization.
dc.identifier.citationSholeh, M. B., Rochim, A. F., & Nugraheni, D. M. K. (2025). Integrating MILP and MCDM for smart warehouse location selection in agricultural e-commerce. Smart Computing and Systems Engineering (SCSE 2025). Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka. (P. 78).
dc.identifier.urihttp://repository.kln.ac.lk/handle/123456789/30395
dc.publisherDepartment of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka.
dc.subjectlocation selection strategy
dc.subjectmixed-integer linear programming
dc.subjectmulti-criteria decision making
dc.subjectoptimization
dc.titleIntegrating MILP and MCDM for Smart Warehouse Location Selection in Agricultural E-Commerce
dc.typeArticle

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