IEEE Access (Jan 2024)

An Effective Discrete Jaya Algorithm for Multi-AGVs Scheduling Problem With Dynamic Unloading Time

  • Yingying Cui,
  • Baoxian Jia,
  • Hongyan Sang,
  • Leilei Meng,
  • Biao Zhang,
  • Wenqiang Zou

DOI
https://doi.org/10.1109/ACCESS.2024.3432594
Journal volume & issue
Vol. 12
pp. 101701 – 101716

Abstract

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With the advance of Automated Guided Vehicles (AGVs) technology, the scheduling of multiple AGVs in a matrix manufacturing workshop has attracted considerable attention. However, little attention has been devoted to dynamic unloading time for multiple AGVs scheduling. This paper investigates a new multi-AGVs scheduling problem with dynamic unloading time (MAGVS $_{\mathrm {DUT}}$ ) in a matrix manufacturing workshop with the objective of minimizing the transportation cost, including travel cost, penalty cost, and vehicle cost. To solve MAGVSDUT, a mixed-integer linear programming model and a discrete Jaya (DJaya) algorithm are proposed. At first, a heuristic based on ant colony algorithm is designed to generate high-quality initial solution. And then, two DJaya operators are designed, one of which is a near optimal operator updating solutions towards better solutions found, while the other is the away worst operator updating solutions towards worst solutions. In addition, a sequence insertion operator is designed to help the population find better solutions within the global space. Finally, a battery of comparative experiments is conducted in conjunction with the actual situation of an electronic equipment manufacturing company. The computational results show that the proposed DJaya algorithm is superior to the existing algorithms in tackling the considered problem.

Keywords