基于改进智能水滴算法的多目标供应链最优模型

Optimal Model of Multi-objective Supply Chain Based on Improved IWD Algorithm

为了最大限度地降低制造型供应链的销售成本并缩短供货时间,提出了一种基于改进智能水滴算法的多目标供应链优化模型。该模型通过在选项选择期间同时考虑成本和时间来提高供应链效率,并能够将制造型供应链中的销售成本和交货时间最小化。通过使用帕累托最优准则对传统的智能水滴算法进行修改,从而得到一个帕累托集,以实现两个目标的最小化。通过3个实例对所提算法进行了测试,并采用世代距离和超区域比指标将其与蚁群优化算法进行了比较。实验结果显示,所提方法的性能更优,生成的解集更接近真实帕累托集,能够覆盖更大的解区域面积,且计算效率较高。

In order to minimize the selling cost and delivery time of manufacturing supply chain,a multi-objective supply chain optimization model based on improved intelligent water drop algorithm was proposed.The model improves the efficiency of the supply chain by considering both cost and time during option selection,and minimizes the sales cost and leads time in the manufacturing supply chain simultaneously.By using the Pareto optimality criterion,the traditional intelligent water drop algorithm is modified to obtain a Pareto set to minimize the two objectives.The algorithm was tested by three examples and compared with the ant colony optimization algorithm using the generation distance and hyperarea ratio index.The results show that the performance of the proposed method is more excellent and the generated set is closer to the real Pareto set to cover a larger area of solution region,with the calculation efficiency being high.