关键词: 交通与运输工程；多中心共同配送与收集; Im-NSGA-Ⅱ算法; 收益分配; 联盟稳定性; 资源配置

Abstract: To overcome the deficiencies of the collaborative alliance construction and profit allocation mechanism design in the multi-center joint distribution and pickup network, an alliance optimization strategy of the multi-center joint distribution and pickup network was proposed. Firstly, a bi-objective optimal model was developed to minimize the total operating cost and the number of vehicles in the network. Secondly, a hybrid heuristic algorithm integrating the k-means clustering algorithm and the improved non-dominated sorting genetic algorithm-Ⅱ (Im-NSGA-Ⅱ) was then proposed to solve the model. Both the idea of the greedy algorithm and the elite retention strategy were introduced in the proposed hybrid heuristic algorithm to improve the global convergence performance and the local optimization capability to search for optimal solutions. In addition, compared with NSGA-Ⅱ and MOGA algorithms, the effectiveness of the proposed algorithm was verified. Thirdly, the minimum costs remaining savings method (MCRS) was exploited to study the profit allocation of the collaborative alliance in the multi-center joint distribution and pickup network, and then the optimal joining sequence selection and the stability of collaborative alliances were discussed. Finally, the proposed model and algorithm were verified by a case study. Results show that the proposed approach can realize the optimal resource distribution in a multi-center joint distribution and pickup network and reduce the total operating cost, which can provide reference and method reference for the optimization of multi-echelon joint distribution and pickup network, and provide decision support for sustainable urban logistics network planning and the construction of shared logistics cooperation alliance.

Key words: traffic and transportation engineering; multi-center joint distribution and pickup network; Im-NSGA-Ⅱ algorithm; profit allocation; alliance stability; resource configuration