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An Effective Discrete Jaya Algorithm for Multi-AGVs Scheduling Problem With Dynamic Unloading Time
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DOI：10.1109/ACCESS.2024.3432594.png)
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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 MAGVS(DUT), 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.
Keyword:
Job shop scheduling
Heuristic algorithms
Manufacturing
Task analysis
Dynamic scheduling
Optimization
Remotely guided vehicles
Matrix manufacturing workshop
multi-AGVs
dynamic unloading time
discrete Jaya algorithm
heuristic
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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[Bayesian Analysis in Expert Systems]: Comment: Graphical Models, Causality and Intervention[专家系统中的贝叶斯分析]: 评论: 图形模型，因果关系和干预
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