多阶段煤炭供应链网络设计及其遗传算法

煤炭供应链网络设计旨在为大型煤炭集团选择合理的设施网络布局与最佳运量,以便提高效率并降低成本。考虑配煤加工与流量平衡等特有约束,建立了煤炭供应链网络混合整数规划模型,其优化目标是最小化固定设施成本、运输总成本与采购成本。考虑到模型求解的复杂度,设计了一种遗传算法,结合优先权与整数规则对染色体进行了编码与解码。实验算例表明所建立的模型能够真实地模拟煤炭供应链网络中设施布局与最佳运量的决策环境,其算法能够在允许的运算时间内获得稳定的满意解,随着算例规模的增大,其计算时间与优化结果均优于LINGO软件。

Genetic algorithm for multi-stage coal supply chain network design

Coal supply chain network design is a strategic issue which aims at selecting the best combination of a set of facilities and flow to achieve an efficient and effective management of the supply chain.Considering the coal blending process and flow balance constraints,a mixed-integer programming model for coal supply chain network is established,so as to minimize the fixed costs of operating and opening logistics centers and coal DCs,the variable transportation costs of raw coal from supplier to logistics centers and the variable transportation costs of the coal blending from logistics centers to customers through coal DCs.Because of its difficulty,a genetic algorithm with priority-based and integer encoding and decoding is designed to obtain the near optimal solutions.Random instances show that the model provides systemic simulation for the whole decision-making process.And the results of GA are stable and acceptable in allowable CPU time.Computational experiments show that the GA heuristic algorithm outperforms LINGO with respect to solution quality and computational time when the instances become larger.