A quantum-inspired Archimedes optimization algorithm for hybrid-load autonomous guided vehicle scheduling problem

Facing the two major challenges of just-in-time (JIT) and energy-saving in part-feeding system for mixed-model assembly lines in automotive industry, this paper focuses on optimizing the part-feeding process by investigating the autonomous guided vehicles (AGV) routing and scheduling problem. A hybr...

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Vydáno v:	Applied intelligence (Dordrecht, Netherlands) Ročník 53; číslo 22; s. 27725 - 27778
Hlavní autoři:	Zhou, Binghai, Zhao, Lingwei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.11.2023 Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Assembly lines Automobile industry Automobiles Automotive parts Computer Science Energy consumption Integer programming Machines Manufacturing Mechanical Engineering Mixed integer Multiple objective analysis Optimization Optimization algorithms Pareto optimum Performance evaluation Processes Scheduling Q-learning AGV scheduling Archimedes optimization algorithm Hybrid part-feeding policy Quantum-inspired algorithm
ISSN:	0924-669X, 1573-7497
On-line přístup:	Získat plný text
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