Optimization of Construction Duration and Schedule Robustness Based on Hybrid Grey Wolf Optimizer with Sine Cosine Algorithm

Mengqi Zhao, Xiaoling Wang, Jia Yu, Lei Bi, Yao Xiao and Jun Zhang
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Mengqi Zhao: State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
Xiaoling Wang: State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
Jia Yu: State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
Lei Bi: CCCC Water Transportation Consultants Co., Ltd., Beijing 100007, China
Yao Xiao: State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
Jun Zhang: State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China

Energies, 2020, vol. 13, issue 1, 1-17

Abstract: Construction duration and schedule robustness are of great importance to ensure efficient construction. However, the current literature has neglected the importance of schedule robustness. Relatively little attention has been paid to schedule robustness via deviation of an activity’s starting time, which does not consider schedule robustness via structural deviation caused by the logical relationships among activities. This leads to a possibility of deviation between the planned schedule and the actual situation. Thus, an optimization model of construction duration and schedule robustness is proposed to solve this problem. Firstly, duration and two robustness criteria including starting time deviation and structural deviation were selected as the optimization objectives. Secondly, critical chain method and starting time criticality (STC) method were adopted to allocate buffers to the schedule in order to generate alternative schedules for optimization. Thirdly, hybrid grey wolf optimizer with sine cosine algorithm (HGWOSCA) was proposed to solve the optimization model. The movement directions and speed of grey wolf optimizer (GWO) was improved by sine cosine algorithm (SCA) so that the algorithm’s performance of convergence, diversity, accuracy, and distribution improved. Finally, an underground power station in China was used for a case study, by which the applicability and advantages of the proposed model were proved.

Keywords: optimization model; construction duration; schedule robustness; critical chain method; STC method; hybrid grey wolf optimizer with sine cosine algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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