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Dynamic Route Optimization and Automation of Industrial Routes at WM

Author

Listed:
  • Hemachandra Pillutla

    (Collection Operations & Business Optimization, WM, Houston, Texas 77002)

  • Seongbae Kim

    (Collection Operations & Business Optimization, WM, Houston, Texas 77002)

  • Chao Zhou

    (Collection Operations & Business Optimization, WM, Houston, Texas 77002)

  • Heesu Hwang

    (Collection Operations & Business Optimization, WM, Houston, Texas 77002)

  • Sergiy Savchenko

    (Collection Operations & Business Optimization, WM, Houston, Texas 77002)

  • Stuart Greene

    (Collection Operations & Business Optimization, WM, Houston, Texas 77002)

  • Marcel Dalby

    (Collection Operations & Business Optimization, WM, Houston, Texas 77002)

Abstract

WM, the leading provider of environmental and sustainability solutions, faced significant challenges in optimizing its industrial waste collection routes following the coronavirus disease 2019 pandemic. Traditionally, these routes were planned manually, a process that was time consuming, labor intensive, and suboptimal with multiple factors that needed to be considered. WM embarked on a journey to develop and implement a dynamic route optimization program tailored to the unique requirements of its industrial waste collection operations. The industrial waste collection sector presents a complex routing problem because of the dynamic nature of customer service demand and several factors, such as customer-specific service requirements, different container types and sizes, and the disposal of waste materials. The dynamic route optimization system leverages data analytics, forecasting future service demand for effective capacity planning, and advanced algorithms using metaheuristics to automate the generation of routes that improve efficiency while ensuring safety and fulfilling customer service commitments. By effectively combining advanced analytics, optimization, and technology-led automation for the industrial line of business, WM realized best-ever efficiency gains and operating margins, and it set the foundations for driving increased value in the future.

Suggested Citation

  • Hemachandra Pillutla & Seongbae Kim & Chao Zhou & Heesu Hwang & Sergiy Savchenko & Stuart Greene & Marcel Dalby, 2026. "Dynamic Route Optimization and Automation of Industrial Routes at WM," Interfaces, INFORMS, vol. 56(1), pages 95-112, January.
    • Handle: RePEc:inm:orinte:v:56:y:2026:i:1:p:95-112
    DOI: 10.1287/inte.2025.0279
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    References listed on IDEAS

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