Multi-objective Assignment Optimization of Port Supply Chain Based on Interval Analysis
【摘要】：Aiming at giving full play to the advantages of enterprise operation under the background of professional division of labor, logistics assignment in the port supply chain is studied. The uncertainty of shipper's demand, unit cost and operating time, which can be described as interval numbers, and an optimization model for port supply chain based on minimization of costs and total operating cycle is established. As the objective function is a nonlinear interval uncertain problem, a double nested genetic algorithm is designed for the assignment problem. In the algorithm, the inner-layer genetic algorithm(IP-GA) is used to solve the objective function interval in the uncertainty domain, while the outer layer is nondominated sorting genetic algorithm(NSGA-Ⅱ). Finally, a case study is given to demonstrate the superiority and feasibility of the proposed algorithm for multi-objective interval optimization.