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A novel location-routing problem in electric vehicle transportation with stochastic demands
- Source :
- Journal of Cleaner Production. 221:567-581
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- With the development of the electric vehicle (EV) technology, the electric vehicle routing problems (EVRPs) have become a current focus for research. Although customer demands in the logistics service industry are often uncertain during the route planning stage, these demands have seldom been discussed in the existing literature on the EVRPs. This study presents an electric vehicle battery swap station (BSS) location-routing problem with stochastic demands, with the aim to determine a minimum cost scheme including the optimal number and location of BSSs with an optimal route plan based on stochastic customer demands. Furthermore, the classical recourse policy and preventive restocking policy are extended by considering the influences of both battery and vehicle capacity simultaneously. Subsequently, the concept of Pareto optimality is applied to the EVRP to expedite the selection of BSS sequences. To solve such a hybrid problem, a hybrid variable neighborhood search (HVNS) algorithm is proposed, which integrates the binary particle swarm optimization and variable neighborhood search to solve the location and routing problems interactively. In experimental studies, the HVNS is compared to five heuristic algorithms to verify its performance.
- Subjects :
- Mathematical optimization
business.product_category
Renewable Energy, Sustainability and the Environment
Computer science
Location routing
020209 energy
Strategy and Management
05 social sciences
Pareto principle
02 engineering and technology
Binary particle swarm optimization
Industrial and Manufacturing Engineering
Optimal route
Electric vehicle
050501 criminology
0202 electrical engineering, electronic engineering, information engineering
Electric-vehicle battery
Route planning
business
Variable neighborhood search
0505 law
General Environmental Science
Subjects
Details
- ISSN :
- 09596526
- Volume :
- 221
- Database :
- OpenAIRE
- Journal :
- Journal of Cleaner Production
- Accession number :
- edsair.doi...........50dc49443de2178ae264e52ca30c4d03