Optimization of supply chain operation cost and gas usage quantity using non-dominated sorting genetic algorithm II (NSGA-II) Method

Abstract

Abstract ABC plant is one of seven plants in XYZ industry which produce Cold Rolling Coil (CRC) and Cold Rolling Sheet (CRS). The problems faced by ABC plant in its supply chain network are the high overall costs of supply chain operations and the quantity of gas usage. The characteristics of this problem consist of more than one objective, the best method for solving this problem called multi-objective optimization. This research is aim to identify the decision variables that will be optimized and determine the optimal quantity of each decision variable using NSGA-II method. The parameters used in this research are the population size of 50, crossover probability with range 0.1-0.9, mutation probability 0.1 and 0.2 also the number of generation 50 and 100. The result shows that the selected parameters for this research are the crossover probability of 0.7, mutation probability of 0.1, number of generation 100. Four decision variables that are optimized, namely CRC produced (Lite, Medium, and Heavy) and CRC stored with the quantities simultaneously are 40,918, 112,479, 173,758, and 43,209 tons. This result will assist the ABC plant in minimizing the overall cost of supply chain (124,532,272 USD) and the quantity of gas usage (39,634,749,440 Kcal).