Solving the Green Open Vehicle Routing Problem Using a Membrane-Inspired Hybrid Algorithm

Yunyun Niu, Zehua Yang, Rong Wen, Jianhua Xiao and Shuai Zhang
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Yunyun Niu: School of Information Engineering, China University of Geosciences in Beijing, Beijing 100083, China
Zehua Yang: School of Information Engineering, China University of Geosciences in Beijing, Beijing 100083, China
Rong Wen: Singapore Institute of Manufacturing Technology, Singapore 138634, Singapore
Jianhua Xiao: The Research Center of Logistics, Nankai University, Tianjin 300071, China
Shuai Zhang: DeGroote School of Business, McMaster University, Hamilton, ON L8S 4M4, Canada

Sustainability, 2022, vol. 14, issue 14, 1-22

Abstract: The green open vehicle routing problem with time windows has been widely studied to plan routes with minimal emissions in third-party logistics. Due to the NP-hardness, the performance of the general heuristics significantly degrades when dealing with large-scale instances. In this paper, we propose a membrane-inspired hybrid algorithm to solve the problem. The proposed algorithm has a three-level structure of cell-like nested membranes, where tabu search, genetic operators, and neighbourhood search are incorporated. In particular, the elementary membranes (level-3) provide extra attractors to the tabu search in their adjacent level-2 membranes. The genetic algorithm in the skin membrane (level-1) is designed to retain the desirable gene segments of tentative solutions, especially using its crossover operator. The tabu search in the level-2 membranes helps the genetic algorithm circumvent the local optimum. Two sets of real-life instances, one of a Chinese logistics company, Jingdong, and the other of Beijing city, are tested to evaluate our method. The experimental results reveal that the proposed algorithm is considerably superior to the baselines for solving the large-scale green open vehicle routing problem with time windows.

Keywords: membrane computing; P system; open vehicle routing problem; carbon emission; tabu search (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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