Collaborative multicenter delivery and pickup network design with transportation resource configuration and alliance synergy service

With the rapid expansion of online shopping platforms, customer demand for parcel delivery and pickup has surged. Logistics alliances, formed through cooperation and resource configuration, offer a more efficient, cost-effective, and sustainable approach for logistics enterprise operations and multicenter logistics network development. However, effectively coordinating synergy services and scheduling transportation resources among alliance members to integrate delivery and pickup activities especially when faced with large-scale and independent demand remains a significant challenge. This study addresses this challenge by proposing and solving a collaborative multicenter delivery and pickup network design problem that incorporates transportation resource configuration and alliance synergy services. First, a measurement function is developed to quantify the alliance synergy degree. Then, a tri-objective optimization model is formulated to maximize alliance synergy while minimizing total operating costs and the number of vehicles. To solve this model, a novel hybrid algorithm is proposed, combining a Gaussian mixture clustering algorithm with an improved multiobjective adaptive large neighborhood search algorithm. This algorithm incorporates multiple removal and insertion operators, as well as an operator weight adaptive adjustment procedure, to improve both global and local search capabilities. Additionally, a transportation resource configuration strategy and an improved α-dominance solution update mechanism are embedded to facilitate vehicle sharing and maintain high-quality Pareto optimal solutions. The effectiveness of the proposed algorithm is demonstrated through comparisons with the CPLEX solver for small-scale problems and with multiobjective genetic algorithm, multiobjective ant colony optimization, and non-dominated sorting genetic algorithm-III for medium-to-large problems. Furthermore, a real-world case study conducted in Chongqing City, China, indicates that the proposed approach can optimize alliance formulation, design open-closed delivery and pickup routes, and enhance synergy and service efficiency. Finally, the effects of different alliance combinations, synergy services, and transportation resource configuration strategies on network optimization are systematically analyzed. This study provides an effective methodology for addressing the multicenter delivery and pickup network design under complex alliance collaboration and resource configuration scenarios, offering valuable insights for improving cost efficiency, resource utilization, and synergy in urban logistics networks.