Article
GA-Based Optimization Method for Mobile Crane
Repositioning Route Planning
Han-Seong Gwak
1,
*, Hong-Chul Lee
2
, Byoung-Yoon Choi
3
and Yirong Mi
3
Citation: Gwak, H.-S.; Lee, H.-C.;
Choi, B.-Y.; Mi, Y. GA-Based
Optimization Method for Mobile
Crane Repositioning Route Planning.
Appl. Sci. 2021, 11, 6010. https://
doi.org/10.3390/app11136010
Academic Editor: João Carlos de
Oliveira Matias
Received: 10 June 2021
Accepted: 25 June 2021
Published: 28 June 2021
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Attribution (CC BY) license (https://
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4.0/).
1
Construction Engineer Policy Institute of Korea, Seoul 06098, Korea
2
Intelligent Construction Automation Center, Kyungpook National University, Daegu 41566, Korea;
colf@knu.ac.kr
3
School of Architecture, Environmental, Energy and Civil Engineering, Kyungpook National University,
Daegu 41566, Korea; jr1381@knu.ac.kr (B.-Y.C.); 2021320938@knu.ac.kr (Y.M.)
* Correspondence: hsgwak@cepik.re.kr; Tel.: +82-2-6240-4336
Abstract:
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.
Keywords: mobile crane; reposition; genetic algorithm; optimization; data modeling
1. Introduction
Cranes are construction equipment that are used to lift loads horizontally or verti-
cally [
1
]. Cranes have been used extensively as essential equipment in construction because
heavy objects are handled frequently at construction sites. Furthermore, as the demand for
large-scale construction projects has increased and the benefits of modular construction
have been recognized, the use of mobile cranes for lifting and installing large modular
materials has also been increasing [
2
]. Mobile cranes have a built-in motor, which allows it
to move to a specific location independently. This makes mobile cranes easier to install,
dismantle, and relocate for lifting work compared to tower cranes.
In modular construction, the mobile crane repeats the task of hanging a load on the
hook and transporting it to the installation location. This requires planning, such as select-
ing an appropriate crane and choosing the crane position while considering productivity
and safety. A careful lift plan is required to perform the lifting work successfully. An im-
proper lift plan may lead to high additional costs and schedule delays [
2
]. Hence, various
studies have been conducted to establish optimal lift plans. These studies can be classified
into three research themes: (1) optimal mobile crane selection [
3
–
6
], (2) investigation on
feasible working areas for mobile cranes [
7
,
8
], and (3) lift path optimization of mobile
cranes [
9
–
15
]. As such, many studies have been conducted on mobile crane operation plans.
However, very few studies have been conducted to investigate the optimal mobile crane
position and travel route.
A mobile crane can lift loads within the working range determined by the boom
length, vehicle size, work safety regulations, etc. [
7
,
13
]. Generally, because the area of a
large site is wider than the working range of the mobile crane, the crane cannot be fixed at
Appl. Sci. 2021, 11, 6010. https://doi.org/10.3390/app11136010 https://www.mdpi.com/journal/applsci
