Collaborative Planning in a Two-Stage Supply Chain: Transparent Coordination, Distributed Response, Integrated Optimization

In the competitive global market, large manufacturing enterprises are striving to achieve a competitive edge through constructing a transparent collaborative supply chain. One of the important and effective ways is to cooperate with distributed response from suppliers in the operation of the supply chain, such as production planning. This article proposes a new collaborative planning mode in a two-stage supply chain considering the supplier part production and product assembly simultaneously. In this context, a mathematical model is formulated and the integrated optimization method is proposed. To reduce the complexity of the problem, the part production decisions of suppliers are first addressed by some lemmas. Then, the transformation process of the mathematical model is described as the decision variables gradually decrease. On this basis, we further propose a LIMA-GVNDS (less is more approach-general variable neighborhood decomposition search) algorithm to solve the integrated supply chain planning problem for the assembly manufacturing enterprise. The objective is to minimize the total supply chain costs. A new neighborhood structure is designed according to the problem characteristics and a series of variable neighborhood descent (VND) variants are proposed. Some computational experiments are carried out, and the results show that the proposed LIMA-GVNDS algorithm has obtained an average 3.69%, 13.07%, 2.47%, and 2.99% improvement of objective value against the other four meta-heuristic algorithms. The model transformation and the integrated optimization method proposed in this article can provide a reference for large manufacturing enterprises to formulate collaborative planning in a transparent supply chain network.