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

IEEE Access, Год журнала: 2024, Номер 12, С. 101701 - 101716

Опубликована: Янв. 1, 2024

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

Язык: Английский

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A lexicographic optimization-based approach for efficient task allocation in industrial transportation multi-robot systems

Expert Systems with Applications, Год журнала: 2024, Номер 257, С. 124998 - 124998

Опубликована: Авг. 22, 2024

Язык: Английский

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Synchronized optimization of the logistics system of a tobacco high-bay warehouse under production task fluctuations

Engineering Research Express, Год журнала: 2024, Номер 6(4), С. 045580 - 045580

Опубликована: Дек. 1, 2024

Abstract Cigarette companies often utilize a logistics system where high-bay warehouse areas for semi-finished and finished tobacco products are located close together linked via trolley tracks. However, fluctuations in production tasks, such as adding new handling emergency orders, canceling existing can introduce challenges to production, including high storage capacity ratios limited transportation capacity. Therefore, this study proposes synchronized optimization method the warehouses designed improve efficiency. A allocation model is developed balance between two tackle ratios. The efficiency improved by minimizing stacker time optimizing shelf center of gravity, with warehouses’ serving key constraints. neural network introduced enhance predicting optimal number trolleys needed each functional area based on task volume, boosting overall Experimental analysis demonstrates that proposed coordinated operation enhances 36.82% 8%. This achieves cigarette enterprises designing shared coordination scheme locations trolleys. Lastly, effectively supports industry addressing dynamic demands provides valuable insights practical engineering applications.

Язык: Английский

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Joint scheduling of hybrid flow-shop with limited automatic guided vehicles: A hierarchical learning-based swarm optimizer

Computers & Industrial Engineering, Год журнала: 2024, Номер 198, С. 110686 - 110686

Опубликована: Ноя. 5, 2024

Язык: Английский

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Ship appointment scheduling for lockage operations of waterway transport with non-punctual arrivals

Ocean Engineering, Год журнала: 2024, Номер 315, С. 119844 - 119844

Опубликована: Ноя. 25, 2024

Язык: Английский

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