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对全球化MTO供应链中一类生产与运输的集成调度问题进行了研究。该问题考虑由单制造商、多客户组成的供应链环境、不同的订单大小、不同的订单复杂度、允许多个订单在单机同时生产以及多种运输方式等现实特征。以最小化供应链总成本为目标,该问题被建模为一个混合整数非线性规划模型;提出了基于前向调度的启发式算法求解该模型。基于真实的行业数据,将该算法的性能与基于遗传算法、顺序调度的方法、以及工业排序方法所产生解的性能进行了比较。比较结果表明,所提出的启发式算法的性能优于后3种方法。
The integrated scheduling problem of a kind of production and transportation in the global MTO supply chain has been studied. This issue considers the realistic characteristics of a supply chain environment consisting of a single manufacturer and a multi-client, different order sizes, different order complexity, simultaneous production of multiple orders in a single machine, and various modes of transportation. To minimize the total cost of the supply chain, the problem is modeled as a mixed-integer nonlinear programming model. A heuristic algorithm based on forward scheduling is proposed to solve the model. Based on real industry data, the performance of this algorithm is compared with that based on genetic algorithms, sequential scheduling, and the performance of solutions produced by the industrial sorting method. The comparison results show that the performance of the proposed heuristic algorithm is better than the latter three methods.