A multi-depot pollution routing problem with time windows in e-commerce logistics coordination

Mengdi Zhang, Aoxiang Chen, Zhiheng Zhao, George Q. Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


Purpose: This research explores mitigating carbon emissions and integrating sustainability in e-commerce logistics by optimizing the multi-depot pollution routing problem with time windows (MDPRPTW). A proposed model contrasts non-collaborative and collaborative decision-making for order assignment among logistics service providers (LSPs), incorporating low-carbon considerations. Design/methodology/approach: The model is substantiated using improved adaptive large neighborhood search (IALNS), tabu search (TS) and oriented ant colony algorithm (OACA) within the context of e-commerce logistics. For model validation, a normal distribution is employed to generate random demand and inputs, derived from the location and requirements files of LSPs. Findings: This research validates the efficacy of e-commerce logistics optimization and IALNS, TS and OACA algorithms, especially when demand follows a normal distribution. It establishes that cooperation among LSPs can substantially reduce carbon emissions and costs, emphasizing the importance of integrating sustainability in e-commerce logistics optimization. Research limitations/implications: This paper proposes a meta-heuristic algorithm to solve the NP-hard problem. Methodologies such as reinforcement learning can be investigated in future work. Practical implications: This research can help logistics managers understand the status of sustainable and cost-effective logistics operations and provide a basis for optimal decision-making. Originality/value: This paper describes the complexity of the MDPRPTW model, which addresses both carbon emissions and cost reduction. Detailed information about the algorithm, methodology and computational studies is investigated. The research problem encompasses various practical aspects related to routing optimization in e-commerce logistics, aiming for sustainable development.

Original languageEnglish
Pages (from-to)85-119
Number of pages35
JournalIndustrial Management and Data Systems
Issue number1
Publication statusPublished - 2 Jan 2024


  • Carbon emission
  • Coordination
  • E-commerce logistics
  • Metaheuristic
  • Pollution routing problem

ASJC Scopus subject areas

  • Management Information Systems
  • Industrial relations
  • Computer Science Applications
  • Strategy and Management
  • Industrial and Manufacturing Engineering


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