Journal
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Volume 40, Issue 3, Pages 5383-5402Publisher
IOS PRESS
DOI: 10.3233/JIFS-202164
Keywords
Vehicle routing problem; time windows; nonlinear charging; differential evolution algorithm
Categories
Funding
- National Science Foundation of China [61773192, 61803192, 61773246]
- Shandong Province Higher Educational Science and Technology Program [J17KZ005]
- Major Program of Shandong Province National Science Foundation [ZR20 18ZB0419]
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This study proposes a hybrid algorithm that combines improved differential evolution and heuristic methods to solve the electric vehicle routing problem with time windows and nonlinear charging constraints. The algorithm takes into account charging station features, integrates battery charging adjustments and negative repair strategies to reduce charging time and ensure feasibility of solutions. The effectiveness of the proposed algorithm is demonstrated through comparison with two efficient algorithms.
This paper investigates the electric vehicle routing problem with time windows and nonlinear charging constraints (EVRPTW-NL), which is more practical due to battery degradation. A hybrid algorithm combining an improved differential evolution and several heuristic (IDE) is proposed to solve this problem, where the weighted sum of the total trip time and customer satisfaction value is minimized. In the proposed algorithm, a special encoding method is presented that considers charging stations features. Then, a battery charging adjustment (BCA) strategy is integrated to decrease the charging time. Furthermore, a novel negative repair strategy is embedded to make the solution feasible. Finally, several instances are generated to examine the effectiveness of the IDE algorithm. The high performance of the IDE algorithm is shown in comparison with two efficient algorithms.
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