Dynamic routing optimization with electric vehicles under stochastic battery depletion


Ünal V., SOYSAL M., ÇİMEN M., Koç Ç.

Transportation Letters, cilt.15, sa.10, ss.1376-1388, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 10
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1080/19427867.2022.2157365
  • Dergi Adı: Transportation Letters
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1376-1388
  • Anahtar Kelimeler: Traveling salesman problem, dynamicity, electric vehicle, stochastic battery depletion, dynamic programming
  • Hacettepe Üniversitesi Adresli: Evet

Özet

© 2022 Informa UK Limited, trading as Taylor & Francis Group.This paper addresses a dynamic traveling salesman problem with electric vehicles under stochastic battery depletion. In the problem, traffic density and battery consumption rate are not known precisely, and their probability distributions are subject to change during the transportation operations. The problem has been formulated and solved using the Dynamic Programming (DP) approach. We develop a DP-based heuristic, which combines Restricted DP and Prim’s algorithms, to solve larger instances. The provided algorithms can determine distribution plans that reduce energy consumption and range anxiety of electric vehicle drivers. The added values of the model and the solution approach have been shown based on a case study and 270 instance-setting pairs that involve relatively larger problems. The heuristic algorithm outperformed a benchmark heuristic by providing 6.87% lower calculated required energy on average. The provided decision support tools can be used to assure energy conservation and emission reduction for short-haul freight distribution systems.