TY - JOUR
ID - 91266
T1 - A Genetic Algorithm with Multiple Populations to Reduce Fuel Consumption in Supply Chain
JO - International Journal of Transportation Engineering
JA - IJTE
LA - en
SN - 2322-259X
A1 - Beheshtinia, Mohammad Ali
A1 - Ahmadi, Bahar
A1 - Fathi, Masood
Y1 - 2019
PY - 2019/07/28
VL -
IS -
SP -
EP -
KW - Transportation
KW - Fuel consumption
KW - Supply chain management
KW - routing
KW - Genetic Algorithm
DO - 10.22119/ijte.2019.134126.1410
N2 - 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.
UR - http://www.ijte.ir/article_91266.html
L1 -
ER -