Composite multi-objective optimization on a new collaborative vehicle routing problem with shared carriers and depots|物流优化数据集|多目标优化数据集

This study proposes a novel logistics collaboration model to address the collaborative vehicle routing problem that involves shared carriers and depots (CVRP-SCD). This is inspired by the fact that a depot often has orders for multiple carriers, and a carrier often delivers orders to multiple depots. This problem involves decreasing transportation distances and improving capacity utilization by extending supply-side unilateral logistics collaborations to simultaneously consider collaborations between supply- and demand-sides. Further, the proposed CVRP-SCD model uses a composite objective that is a weighted sum of four objectives — including quality, reliability, cost, and time — to accurately evaluate and analyze the efficiency improvement. An extended variable neighborhood search algorithm is presented based on three matrices, including the carrier collaboration matrix, depot collaboration matrix, and transportation sequence matrix. This algorithm aims to address the trade-offs among multiple objectives for the CVRP-SCD problem by incorporating new operators based on specific features involved in the problem.