关键词: 物流工程, 合整数规划模型, 遗传算法, 复杂需求, 配煤加工, 煤炭供应链

Abstract: Because there are some major differences in coal product’s quality among different coal equipment’s requirements, it is necessary to carry out coal blending process with different kinds of coal, so as to meet customer individual requirements and reduce the environment pollution. Considering these complex characteristics, coal blending process and flow balance constraints, a new mixed-integer programming model for four-echelon coal supply chain network is established, in order to decide the number of various facilities, their locations and scales, and the allocation of the corresponding logistics flows. Because it is NP-hard in nature, a genetic algorithm with a new encoding structure is designed, and the initial population are created by greedy heuristics to accelerate the convergence of GA. Random instances show that the solution quality of GA is superior to hybrid GA and simulated annealing. Meanwhile, the GA outperforms LINGO software with respect to computational time when the instances become larger.

Key words: logistics engineering, mixed-integer programming model, genetic algorithm, complex demands, coal blending process, coal supply chain