The Multi-Depot Traveling Purchaser Problem with Shared Resources

Abstract

Using shared resources has created better opportunities in the field of sustainable logistics and procurement. The Multi-Depot Traveling Purchaser Problem under Shared Resources (MDTPPSR) is a new variant of the Traveling Purchaser Problem (TPP) in sustainable inbound logistics. In this problem, each depot can purchase its products using the shared resources of other depots, and vehicles do not have to return to their starting depots. The routing of this problem is a Multi-Trip, Open Vehicle Routing Problem. A tailored integer programming model is formulated to minimize the total purchasers’ costs. Considering the complexity of the model, we have presented a decomposition-based algorithm that breaks down the problem into two phases. In the first phase, tactical decisions regarding supplier selection and the type of collaboration are made. In the second phase, the sequence of visiting is determined. To amend the decisions made in these phases, two heuristic algorithms based on the removing and insertion of operators are also proposed. The experimental results show that not only can purchasing under shared resources reduce the total cost by up to 29.11%, but it also decreases the number of dispatched vehicles in most instances.

A Novel Two-Phase Approach for Optimization of the Last-Mile Delivery Problem with Service Options

“…To the best of our knowledge, there is no specific dataset in the literature that is relevant to our proposed research (VRPSO). Based on a uniform distribution, the pickup and delivery points and depot locations are distributed in a [0, 1000] [0, 1000] square [64]. Through the EUC_2D function in TSPLIB [65], routing costs are also calculated by Euclidean distances.…”

Designing a Fuzzy Mathematical Model for a Two-Echelon Allocation-Routing Problem by Applying Route Conditions: A New Interactive Fuzzy Approach

“…A hybrid algorithm combining an improved k-medoids clustering algorithm and multi-objective particle swarm optimization (PSO) is presented to solve the proposed model and obtain near-optimum solutions. Hasanpour Jesri et al, [29] have addressed the Multi-Trip Open Vehicle Routing Problem (MTOVRP). They formulated an appropriate integer programming model to minimize the total costs of buyers.…”

A Hybrid Adaptive Simulated Annealing and Tempering Algorithm for Solving the Half-Open Multi-Depot Vehicle Routing Problem

“…Wang et al [9] proposed a two-stage hybrid meta-heuristic algorithm combining customer clustering and vehicle path optimization: customers are reassigned to logistics facilities by an improved 3D k-means clustering algorithm and then a hybrid meta-heuristic algorithm combining a genetic algorithm and a particle swarm optimization algorithm is designed. Hasanpour Jesri et al [28] studied the multi-warehouse traveling purchaser problem with half-open vehicle paths in the context of shared resources and proposed a decomposition-based two-stage heuristic algorithm to solve it. Bai et al [29] studied a bike rebalancing problem that allows vehicles to return to different depots and a hybrid heuristic algorithm based on variable neighborhood search and dynamic programming to solve it.…”

“…Algorithms for the HOMDVRP and its variants have primarily focused on hybrid meta-heuristic algorithms and hybrid heuristic algorithms. However, most of the studies focus on the significance of half-open paths for the improvement in MDVRP based on practical logistics scenarios [9,23,24,28], while there is a lack of algorithmic studies based on the key structural features of HOMDVRP [22,25,27]. This lack of consideration leads to the algorithms for solving the HOMDVRP easily falling into local optimum or unacceptable computational time.…”