Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective

Lei Cao, Chun ming Ye, Ran Cheng, Zhen kun Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

12 Citations (Scopus)

Abstract

A business delivery model with professional vehicles as well as occasional passing-by vehicles is investigated in this paper. The drivers deliver parcels from the distribution center to customers and the passing-by driver can get a certain amount of compensation in return. To give a satisfactory solution from the perspective of platform owner, customers, professional drivers, occasional drivers, and authority, a multi-layer comprehensive model is proposed. To effectively solve the proposed model, we introduce an improved variable neighborhood search (VNS) with a memory-based restart mechanism. The new algorithm is evaluated on instances derived from Solomon’s benchmark and real-life beer delivery instances. Taguchi experiment is used to tune parameters in the proposed VNS, followed by component analysis and real-life experiments. Experimental results indicate that the proposed strategies are effective and the new delivery model in this paper has some advantages over traditional and single-delivery ones from the comprehensive perspectives of stakeholders in the crowdsourcing logistics system.

Original languageEnglish
Pages (from-to)2507-2525
Number of pages19
JournalComplex and Intelligent Systems
Volume8
Issue number3
DOIs
Publication statusPublished - Jun 2022
Externally publishedYes

Keywords

  • City logistics
  • Crowdsourcing
  • Memory programming
  • Variable neighborhood search

ASJC Scopus subject areas

  • Information Systems
  • Engineering (miscellaneous)
  • Computational Mathematics
  • Artificial Intelligence

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