GA-Based Optimization Method for Mobile Crane Repositioning Route Planning

Mobile cranes have been used extensively as essential equipment at construction sites. The productivity improvement of the mobile crane affects the overall productivity of the construction project. Hence, various studies have been conducted regarding mobile crane operation planning. However, studies...

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Main Authors: Han-Seong Gwak, Hong-Chul Lee, Byoung-Yoon Choi, Yirong Mi
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/13/6010
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spelling doaj-81a5858071734533b3be7edf20691cf12021-07-15T15:30:19ZengMDPI AGApplied Sciences2076-34172021-06-01116010601010.3390/app11136010GA-Based Optimization Method for Mobile Crane Repositioning Route PlanningHan-Seong Gwak0Hong-Chul Lee1Byoung-Yoon Choi2Yirong Mi3Construction Engineer Policy Institute of Korea, Seoul 06098, KoreaIntelligent Construction Automation Center, Kyungpook National University, Daegu 41566, KoreaSchool of Architecture, Environmental, Energy and Civil Engineering, Kyungpook National University, Daegu 41566, KoreaSchool of Architecture, Environmental, Energy and Civil Engineering, Kyungpook National University, Daegu 41566, KoreaMobile cranes have been used extensively as essential equipment at construction sites. The productivity improvement of the mobile crane affects the overall productivity of the construction project. Hence, various studies have been conducted regarding mobile crane operation planning. However, studies on solving RCP (the repositioning mobile crane problem) are insufficient. This article presents a mobile crane reposition route planning optimization method (RPOS) that minimizes the total operating time of mobile crane. It converts the construction site into a mathematical model, determines feasible locations of the mobile crane, and identifies near-global optimal solution (s) (i.e., the placement point sequences of mobile crane) by implementing genetic algorithm and dijkstra’s algorithm. The study is of value to practitioners because RPOS provides an easy-to-use computerized tool that reduces the lengthy computations relative to data processing and Genetic Algorithms (GAs). Test cases verify the validity of the computational method.https://www.mdpi.com/2076-3417/11/13/6010mobile cranerepositiongenetic algorithmoptimizationdata modeling
collection DOAJ
language English
format Article
sources DOAJ
author Han-Seong Gwak
Hong-Chul Lee
Byoung-Yoon Choi
Yirong Mi
spellingShingle Han-Seong Gwak
Hong-Chul Lee
Byoung-Yoon Choi
Yirong Mi
GA-Based Optimization Method for Mobile Crane Repositioning Route Planning
Applied Sciences
mobile crane
reposition
genetic algorithm
optimization
data modeling
author_facet Han-Seong Gwak
Hong-Chul Lee
Byoung-Yoon Choi
Yirong Mi
author_sort Han-Seong Gwak
title GA-Based Optimization Method for Mobile Crane Repositioning Route Planning
title_short GA-Based Optimization Method for Mobile Crane Repositioning Route Planning
title_full GA-Based Optimization Method for Mobile Crane Repositioning Route Planning
title_fullStr GA-Based Optimization Method for Mobile Crane Repositioning Route Planning
title_full_unstemmed GA-Based Optimization Method for Mobile Crane Repositioning Route Planning
title_sort ga-based optimization method for mobile crane repositioning route planning
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2021-06-01
description Mobile cranes have been used extensively as essential equipment at construction sites. The productivity improvement of the mobile crane affects the overall productivity of the construction project. Hence, various studies have been conducted regarding mobile crane operation planning. However, studies on solving RCP (the repositioning mobile crane problem) are insufficient. This article presents a mobile crane reposition route planning optimization method (RPOS) that minimizes the total operating time of mobile crane. It converts the construction site into a mathematical model, determines feasible locations of the mobile crane, and identifies near-global optimal solution (s) (i.e., the placement point sequences of mobile crane) by implementing genetic algorithm and dijkstra’s algorithm. The study is of value to practitioners because RPOS provides an easy-to-use computerized tool that reduces the lengthy computations relative to data processing and Genetic Algorithms (GAs). Test cases verify the validity of the computational method.
topic mobile crane
reposition
genetic algorithm
optimization
data modeling
url https://www.mdpi.com/2076-3417/11/13/6010
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AT byoungyoonchoi gabasedoptimizationmethodformobilecranerepositioningrouteplanning
AT yirongmi gabasedoptimizationmethodformobilecranerepositioningrouteplanning
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