Flexible time–space network formulation and hybrid metaheuristic for conflict-free and energy-efficient path planning of automated guided vehicles

Jianbin Xin, Liuqian Wei, Andrea D'Ariano, Fangfang Zhang*, Rudy Negenborn

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
49 Downloads (Pure)

Abstract

Operations of Automated Guided Vehicles (AGVs) are desired to be more energy-efficient while maintaining high transport productivity, motivated by the green production requirements. This paper investigates a new energy-efficient planning problem for determining conflict-free paths of the AGVs in its transport roadmap. In this problem, the vehicle path and transport time in the roadmap are jointly optimized, based on a flexible time–space network (FTSN). We provide the mathematical problem formulation of the energy-efficient path planning problem. The resulting optimization problem is proved to be a non-convex mixed-integer nonlinear programming which is computationally intractable. We further propose a hybrid metaheuristic that integrates the genetic algorithm and estimation of the distribution algorithm to improve its computational efficiency. Numerical results show the effectiveness of the developed algorithm based on the FTSN framework, compared to the existing metaheuristics, the conventional path planning method, and a commercial solver. The proposed method has a wide application in improving energy use of material handling, providing a guiding significance on promoting cleaner production of flexible manufacturing systems.

Original languageEnglish
Article number136472
Number of pages13
JournalJournal of Cleaner Production
Volume398
DOIs
Publication statusPublished - 2023

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Automated guided vehicles
  • Energy efficiency
  • Flexible time–space network model
  • Hybrid metaheuristic

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