A parallel Lagrange algorithm for order acceptance and scheduling in cluster supply chains

摘要

In a single supply chain scenario, orders are likely to be refused for lack of insufficient capacity and production time. In this paper, cluster supply chains (a kind of multiple supply chains, short for CSC) is introduced to avoid this potential operational risk via across-chain cooperation, which is not considered in any previous work. First, the framework of order selection in cluster supply chain (CSC) is presented based on four order categories (direct order, reserve order, across-chain order and rejected order), followed by that the model without and with across-chain cooperation in cluster supply chains are proposed to aid operational managers to make joint decision regarding order acceptance and scheduling under maximizing the overall profit. Considering the complexity of cluster supply chains structure and a mass of data from actual operations, a parallel Lagrange heuristic algorithm is devised to solve the Mixed-Integer Non-Linear Program (MINLP) problem. Meanwhile, Benders algorithm is utilized to compare with it for evaluating performance. The result proves the parallel Lagrange heuristic algorithm outperforms Benders approach, the former can efficiently solve large-scale-data problem instances at relatively short time. The outcomes also reveal that, by designing the different combination of the factor of rejected order and that of across-chain order, it can be better trade-off between order due-date and cost while better aligning with the long-term business strategy in cluster supply chains.