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Optimization of human-aware logistics and manufacturing systems: A survey on the Human-Aware Models

  • Blaise Pascal University
  • Mines Saint-Etienne
  • UMR CNRS 6597
  • Université de Lille

Research output: Contribution to journal › Review article › peer-review

13 Citations (Scopus)

Abstract

Historically, Operations Research (OR) discipline has mainly been focusing on economic concerns. Since the early 2000s, human considerations are gaining increasing attention, pushed by the growing societal concerns of sustainable development on the same terms as the economic and ecological ones. This paper is the second part of a work that aims at reviewing the efforts dedicated by the OR community to the integration of human aspects into logistics and manufacturing systems. A focus is put on the models proposed to represent and quantify human characteristics, their practical relevance, and the complexity induced by their integration with mathematical optimization models. In this paper, the techniques used in the OR literature to represent the human considerations encountered in logistics and manufacturing systems are surveyed. The existing Human-Aware Models (HAM) are classified and reviewed by domain. Particular attention is paid to the field validity of each method, its relevance to specific use cases, the required data collection, and its usability within mathematical optimization models. Since the surveyed HAMs rely on concepts originating from different related scientific disciplines (e.g., ergonomics, occupational medicine), a brief introduction of these fields of study is proposed together with a work of contextualization that is carried out during the analysis.

Original languageEnglish
Article number100137
JournalEURO Journal on Transportation and Logistics
Volume13
DOIs
Publication statusPublished - 1 Jan 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Ergonomics
  • Human factors
  • Logistics
  • Manufacturing
  • Optimization

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