Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/310075 
Year of Publication: 
2018
Citation: 
[Journal:] Logistics [ISSN:] 2305-6290 [Volume:] 2 [Issue:] 3 [Year:] 2018 [Pages:] 1-16
Publisher: 
MDPI, Basel
Abstract: 
This paper presents a methodology to solve a special case of the vehicle routing problem (VRP) called the heterogeneous fleets VRP with excessive demand of the vehicle at the pickup points, and the longest time constraint (HFVRP-EXDE-LTC). We developed two metaheuristics-a differential evolution (DE) algorithm and an adaptive large neighborhood search (ALNS)-to solve the problem. These two proposed methods have been designed to effectively solve a special case of VRP. From the computational results, we can see that the proposed heuristics outperformed the best practices that are currently in use. The DE yielded a 9.78% lower cost than that of the current practice (757,250 baht per year), while ALNS generated a 10.89% (906,750 baht per year) lower cost than that of current practice. Comparing the proposed heuristics, ALNS achieved a 1.01% lower cost than that of DE, as ALNS had a better mechanism that was designed to escape from the local optimal.
Subjects: 
vehicle routing problem
adaptive large neighborhood search
differential evolution algorithm
pickup and delivery system
school bus
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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