Document Type : Research Paper
Associate Professor, Industrial Engineering Department, Semnan University, Semnan, Iran
MSc. Grad., Department of Industrial Engineering, , Semnan University, Semnan, Iran
Assistant Professor, Department of Production and Automation Engineering, University of Skövde, Skövde, Sweden
Reducing fuel consumption by transportation fleet in a supply chain, reduces transportation costs and consequently, the product final cost. Moreover, it reduces environmental pollution, and in some cases, it helps governments constitute less subsidies for fuels. In this paper, a supply chain scheduling is studied, with the two objective functions of minimizing the total fuel consumption, and the total order delivery time. After presenting the mathematical model of the problem, a genetic algorithm, named Social Genetic Algorithm (SGA) is proposed to solve it. The proposed algorithm helps decision makers determine the allocation of orders to the suppliers and vehicles and production and transportation scheduling to minimize total order delivery time and fuel consumption. In order for SGA performance evaluation, its results are compared with another genetic algorithm in the literature and optimal solution. Finally, a sensitivity analysis is performed on SGA. The results of comparisons also show the high performance of SGA. Moreover, by increasing the number of suppliers and vehicles and decreasing the number of orders, the value of the objective function is reduced.