Simulation-Based Optimization Approaches for Dealing with Dual-Command Crane Scheduling Problem in Unit-Load Double-Deep AS/RS Considering Energy Consumption
Automated storage/retrieval systems (AS/RS) have been increasingly used to support operations in manufacturing firms, warehouses, and distribution centers. Usually, AS/RSs are expensive. To achieve a good return on investment (ROI), an AS/RS must operate optimally. This research focuses on solving t...
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MDPI AG
2022-10-01
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author | Hsien-Pin Hsu Chia-Nan Wang Thanh-Tuan Dang |
author_facet | Hsien-Pin Hsu Chia-Nan Wang Thanh-Tuan Dang |
author_sort | Hsien-Pin Hsu |
collection | DOAJ |
description | Automated storage/retrieval systems (AS/RS) have been increasingly used to support operations in manufacturing firms, warehouses, and distribution centers. Usually, AS/RSs are expensive. To achieve a good return on investment (ROI), an AS/RS must operate optimally. This research focuses on solving the crane scheduling problem, which has a great and immediate impact on the performance of an AS/RS. To optimize the design and operations of an AS/RS, many past studies have applied the simulation approach. However, the simulation and optimization have been often loosely coupled, resulting in a rigorous and labor-intensive optimization procedure. Using population- and evolution-based metaheuristics to deal with the crane scheduling problem of an AS/RS is one of the research trends. However, the whale optimization algorithm (WOA) and its variants have not been used for this purpose. To address the said gaps, this research first proposes a framework for coupling the simulation and optimization closely, in which various heuristics/metaheuristics, including first-come first-serve (FCFS), RANDOM, WOA, genetic algorithms (GAs), particle swarm optimization (PSO), and especially an improved WOA (IWOA), together with dynamic programming (DP), have been used as alternative sequencing methods. Based on this framework, different simulation-based optimization approaches have been developed for solving the dual-command crane scheduling problem in a unit-load double-deep AS/RS. The experimental results show that IWOA+DP outperforms the others in terms of energy consumption. |
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issn | 2227-7390 |
language | English |
last_indexed | 2024-03-09T18:52:12Z |
publishDate | 2022-10-01 |
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spelling | doaj.art-b6bd78fd59db4be6ae976d241af549402023-11-24T05:43:39ZengMDPI AGMathematics2227-73902022-10-011021401810.3390/math10214018Simulation-Based Optimization Approaches for Dealing with Dual-Command Crane Scheduling Problem in Unit-Load Double-Deep AS/RS Considering Energy ConsumptionHsien-Pin Hsu0Chia-Nan Wang1Thanh-Tuan Dang2Department of Supply Chain Management, National Kaohsiung University of Science and Technology, Kaohsiung 81157, TaiwanDepartment of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 807618, TaiwanDepartment of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh 72320, VietnamAutomated storage/retrieval systems (AS/RS) have been increasingly used to support operations in manufacturing firms, warehouses, and distribution centers. Usually, AS/RSs are expensive. To achieve a good return on investment (ROI), an AS/RS must operate optimally. This research focuses on solving the crane scheduling problem, which has a great and immediate impact on the performance of an AS/RS. To optimize the design and operations of an AS/RS, many past studies have applied the simulation approach. However, the simulation and optimization have been often loosely coupled, resulting in a rigorous and labor-intensive optimization procedure. Using population- and evolution-based metaheuristics to deal with the crane scheduling problem of an AS/RS is one of the research trends. However, the whale optimization algorithm (WOA) and its variants have not been used for this purpose. To address the said gaps, this research first proposes a framework for coupling the simulation and optimization closely, in which various heuristics/metaheuristics, including first-come first-serve (FCFS), RANDOM, WOA, genetic algorithms (GAs), particle swarm optimization (PSO), and especially an improved WOA (IWOA), together with dynamic programming (DP), have been used as alternative sequencing methods. Based on this framework, different simulation-based optimization approaches have been developed for solving the dual-command crane scheduling problem in a unit-load double-deep AS/RS. The experimental results show that IWOA+DP outperforms the others in terms of energy consumption.https://www.mdpi.com/2227-7390/10/21/4018automated storage and retrieval (AS/RS)metaheuristicswhale optimization algorithm (WOA)crane scheduling problem |
spellingShingle | Hsien-Pin Hsu Chia-Nan Wang Thanh-Tuan Dang Simulation-Based Optimization Approaches for Dealing with Dual-Command Crane Scheduling Problem in Unit-Load Double-Deep AS/RS Considering Energy Consumption Mathematics automated storage and retrieval (AS/RS) metaheuristics whale optimization algorithm (WOA) crane scheduling problem |
title | Simulation-Based Optimization Approaches for Dealing with Dual-Command Crane Scheduling Problem in Unit-Load Double-Deep AS/RS Considering Energy Consumption |
title_full | Simulation-Based Optimization Approaches for Dealing with Dual-Command Crane Scheduling Problem in Unit-Load Double-Deep AS/RS Considering Energy Consumption |
title_fullStr | Simulation-Based Optimization Approaches for Dealing with Dual-Command Crane Scheduling Problem in Unit-Load Double-Deep AS/RS Considering Energy Consumption |
title_full_unstemmed | Simulation-Based Optimization Approaches for Dealing with Dual-Command Crane Scheduling Problem in Unit-Load Double-Deep AS/RS Considering Energy Consumption |
title_short | Simulation-Based Optimization Approaches for Dealing with Dual-Command Crane Scheduling Problem in Unit-Load Double-Deep AS/RS Considering Energy Consumption |
title_sort | simulation based optimization approaches for dealing with dual command crane scheduling problem in unit load double deep as rs considering energy consumption |
topic | automated storage and retrieval (AS/RS) metaheuristics whale optimization algorithm (WOA) crane scheduling problem |
url | https://www.mdpi.com/2227-7390/10/21/4018 |
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