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Efficient multiobjective optimization for an AGV energy-efficient scheduling problem with release time
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AI
DOI：10.1016/j.knosys.2022.108334.png)
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Abstract
En 中文
In recent years, green manufacturing has attracted wide attention from researchers. However, the energy efficiency problem in matrix manufacturing workshops is still a blank area. This paper considers a novel automatic guided vehicle (AGV) energy-efficient scheduling problem with release time (AGVEESR) to optimize the three objectives of energy consumption, number of AGVs used and customer satisfaction simultaneously. Considering the development of the AGVEESR, we extract problem-specific knowledge, establish a multiobjective mathematical model, and design a hybrid constructive heuristic. Due to the complexity of the problem, we propose an efficient multiobjective greedy algorithm (MOGA) with effective strategies such as new population initialization, greedy operation, and self-adaptive multiple neighbourhood local search. Meanwhile, an ideal-point-based construction operator in the greedy operation phase is presented to lower the computational complexity. Simulation results show that the proposed MOGA has a tremendously superior performance to the five state-of-the-art algorithms in solving the problem considered. (c) 2022 Elsevier B.V. All rights reserved.
Keywords:
Multiobjective optimization
Automated guided vehicle
Energy efficiency
Release time
Matrix manufacturing workshop
Journal
K
IF:
7.6
Papers:
1.2W
Citations:
4.5W