Stackelberg game optimization for integrated production-distribution-construction system in construction supply chain

Although construction supply chain management has attracted significant research attention, this field remains somewhat fragmented. This paper examines an integrated production-distribution-construction system consisting of the construction department and material suppliers under a fuzzy random environment with the aim of optimizing the global equilibrium. A novel bi-level multistage programming method with multiple objective optimization is developed to examine the inherent conflicts and complex interactions among decision makers in order to obtain the Stackelberg-Nash equilibrium solution, in which the construction department, as the leader, decides on the material allocations to construction sites, while the material supplier, as the follower, produces and transports the corresponding materials. For dealing with uncertainties, a hybrid crisp approach with an expected value operator is proposed to convert the fuzzy random parameters into definitive parameters. A hybrid algorithm combining an evolved genetic algorithm and particle swarm optimization is developed to solve this novel Stackelberg game model. The results from a practical example demonstrate the practicality and efficiency of the proposed optimization method, highlight the significance of quantitative analysis for the construction supply chain, and provide objective guidelines for its real-world application.