Optimizing Joint Production Planning, Pricing and Retailer Selection with Emission Control based on Stackelberg Game and Nested Genetic Algorithm

摘要

We address the joint decision making of production planning, pricing, and retailer selection while considering emission control. In view of the interactive decision-making processes, we adopt the Stackelberg game theory and develop a 0-1 mixed nonlinear bi-level programming model to maximize the profits of a manufacturer and his retailers. Involving two submodels representing the decision-making processes of the manufacturer and retailers, respectively, the Stackelberg game model is very complex and impossible to be solved analytically. Therefore, we further develop a nested genetic algorithm (NGA) to solve the game model. Numerical examples demonstrate (i) the applicability of the Stackelberg game model in making joint decisions and (ii) the robustness of the NGA. Sensitivity analysis sheds light on several important managerial implications.