Application of Multiagent Technologies to Multiple Depot Vehicle Routing Problem with Time Windows

Сазонов, В В; Skobelev, Petr; Lada, Alexander; Mayorov, Igor

doi:10.1134/s0005117918060127

Cited by 8 publications

(2 citation statements)

References 6 publications

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“…Finally, the optimal performance of GA was verified. Sazonov V et al [15] established a multi-agent system with the interaction of trucks, warehouses and orders to solve the MDVRPTW. To limit the intensity of negotiations, a Delaunay triangulationbased scene structure was proposed.…”

Section: B Multi-depots Vehicle Routing Problem With Time Windows (Md...mentioning

confidence: 99%

Route Planning for Chain Restaurants With Improved Delivery Mode Using an Adaptive Genetic Algorithm

Cao

2022

IEEE Access

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With the popularization of logistics technology and the improvement of people ' s living standards, the number of chain restaurants with delivery service is increasing continuously due to the convenient service and special discounts. However, the inappropriate management mode and delivery delays often lead to high delivery cost, especially during the peak meal period. Therefore, to solve the problems, two delivery modes, Modern Delivery Mode of Chain Restaurants (MDMCR) and Improved Delivery Mode of Chain Restaurants (IDMCR) were first proposed. IDMCR is an one-stage approach to directly solve the delivery routing problem of multiple branches. Furthermore, we presented an adaptive genetic algorithm for delivery of chain restaurants (AGA-DCR) specifically for IDMCR, which adjusts adaptively the traditional crossover and mutation operations to the fitness of individual and population, therefore, local optimal is avoid. The experiments were conducted with the same dataset to compare different approaches. The results demonstrated that AGA-DCR avoided falling into the local optimal while improved the quality of the solution. Moreover, IDMCR combined with AGA-DCR achieved the best performance, reducing the delivery delay cost by 56.2% compared to MDMCR with GA. Additionally, the optimal delivery routes for chain restaurants were visualized to provide a reference solution for the practical applications.INDEX TERMS adaptive genetic algorithm, chain restaurants delivery, multi-depot vehicle routing problem, vehicle routing.

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Section: B Multi-depots Vehicle Routing Problem With Time Windows (Md...mentioning

confidence: 99%

Route Planning for Chain Restaurants With Improved Delivery Mode Using an Adaptive Genetic Algorithm

Cao

2022

IEEE Access

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“…In this article, we assume that there are 64 turbines in one cluster and 16 of them need to be maintained in the next 7 days planning horizon based on the recommended period in which the turbines need to be serviced. Three O&M logistics bases (Wang et al, 2019;Sazonov et al, 2018) owning resources such as vessels, technicians and warehouses are located around the wind farms with different distances.…”

Section: System Description Of Offshore Wind Farmsmentioning

confidence: 99%

A hybrid heuristic optimization of maintenance routing and scheduling for offshore wind farms

Fan

Ren

Zhu

et al. 2019

Journal of Loss Prevention in the Process Industries

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As the operation and maintenance (O&M) costs constitute a substantial portion of the overall life-cycle cost of offshore wind farms, routing, and scheduling of maintenance are very important for cost reduction. With the multi-type of vessels, multi-period, multi-base of O&M, multi-wind farm and uncertain weather conditions, the optimization of O&M cost is more challenging. In this article, a hybrid heuristic optimization of maintenance routing and scheduling for offshore wind farms is proposed. First, with the maintenance service protocol, mixed particle swarm optimization (MPSO) is applied to seek a desired mapping relation between vessels and wind farms. Utilizing the formalized rules, an optimal vessel allocation scheme is explored in the large solution space by individual crossover, swarm crossover and mutation. Then, with the scheme of vessel allocation, a discrete wolf pack search (DWPS) is introduced to optimize the maintenance route under all constraints. As the evaluation standard of MPSO, the purpose of DWPS is to search the solution space with depth and breadth balanced and find the optimal and open maintenance route with multiple round trips to bases that minimize O&M costs, including travel, technician and penalty costs. Finally, computational experiments and analysis are carried out. The results provide both the optimized cost and detailed arrangements, which can be directly used in the maintenance schedule.

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Migratory beekeeping routing: a combinatorial optimization problem in apiculture

Qiu,

Gajpal,

Roy

et al. 2024

Ann Oper Res

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Application of Multiagent Technologies to Multiple Depot Vehicle Routing Problem with Time Windows

Cited by 8 publications

References 6 publications

Route Planning for Chain Restaurants With Improved Delivery Mode Using an Adaptive Genetic Algorithm

Route Planning for Chain Restaurants With Improved Delivery Mode Using an Adaptive Genetic Algorithm

A hybrid heuristic optimization of maintenance routing and scheduling for offshore wind farms

Migratory beekeeping routing: a combinatorial optimization problem in apiculture

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