Barış KaradenizMehmet Serdar ErdoğanYigit KazancogluN.M. Durakbasa , M.G. Gençyılmaz2025-10-0620229789819650583, 9783031991585, 9783031948886, 9789819667314, 9789811937156, 9783030703318, 9789811622779, 9789811969447, 9789819701056, 978981974805121954364, 2195435610.1007/978-3-030-90421-0_70https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119888858&doi=10.1007%2F978-3-030-90421-0_70&partnerID=40&md5=56b05acadcb5729979440878420ec983https://gcris.yasar.edu.tr/handle/123456789/8847In this study we designed a vehicle routing problem model for chocolate manufacturer company to optimize their distribution system. Our model includes 3 warehouses heterogenous fleet multi period and about two dozen customers. We got our customer data directly from company. We considered distance between the customers their demands and vehicle capacities. Sensitivity analysis was made to make sure that it is effective. In the model that we designed we compared 10-15-20 customer cases with 3 depot 1 depot heterogeneous and homogeneous fleet scenarios. According to results of the study homogeneous fleet scenarios are costly. In addition using single depot is costly than using multiple depots. © 2022 Elsevier B.V. All rights reserved.EnglishHeterogeneous Fleet, Mixed-integer Linear Programming, Multi Depot, Optimization, Vehicle Routing Problem, Fleet Operations, Integer Programming, Sales, Vehicle Routing, Vehicles, Case-studies, Heterogeneous Fleet, Integer Linear Programming, Mixed Integer Linear, Mixed-integer Linear Programming, Multi Depots, Multi-period, Optimisations, Real Case, Vehicle Routing Problems, Sensitivity AnalysisFleet operations, Integer programming, Sales, Vehicle routing, Vehicles, Case-studies, Heterogeneous fleet, Integer Linear Programming, Mixed integer linear, Mixed-integer linear programming, Multi depots, Multi-period, Optimisations, Real case, Vehicle Routing Problems, Sensitivity analysisConference Object