Developing Shuffled Frog-Leaping Algorithm (SFLA) Method to Solve Power Load-Constrained TCRTO Problems in Civil Engineering

Author:

Tao Xingyu1,Li Heng2,Mao Chao3,Wang Chen45ORCID,Hui Yap Jeffrey Boon6,Sepasgozar Samad7,Shirowzhan Sara8,Rose Timothy9

Affiliation:

1. School of Construction Management and Real Estate, Chongqing University, Chongqing 400044, China

2. Chair Professor of Construction Informatics, Department of Building and Real Estate, Faculty of Construction and Environment, Hong Kong Polytechnic University, Room No. ZS734, Hung Hom, Kowloon, Hong Kong

3. Associate Professor, School of Construction Management and Real Estate, Chongqing University, Room No. 504, Chongqing 400044, China

4. Professor, College of Civil Engineering, Huaqiao University, 361021 Xiamen, China

5. Director of Intelligence and Automation in Construction Fujian Province Higher-Educational Engineering Research Centre, 361021 Xiamen, China

6. Assistant Professor, Department of Surveying, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman (UTAR), 43000 Kajang, Selangor, Malaysia

7. Senior Lecturer, Faculty of Built Environment, University of New South Wales Sydney, Kensington, Australia

8. Research Fellow, Faculty of Built Environment, University of New South Wales Sydney, Kensington, Australia

9. Senior Lecturer, Faculty of Science and Engineering, Queensland University of Technology, Brisbane, Australia

Abstract

It is extensively acknowledged that excessive on-site electricity power load often causes power failure across a construction site and surrounding residential zones and can result in unforeseen schedule delay, construction quality problems, life inconvenience, and even property loss. However, energy management, such as power load optimization, has long been ignored in construction scheduling. This study aims to develop a modified shuffled frog-leaping algorithm (SFLA) approach in project scheduling to aid decision-makers in identifying the best Pareto solution for time-cost-resource trade-off (TCRTO) problems under the constraint of precedence, resource availability, and on-site peak electricity power load. A mathematical model including three objective functions and five constraints was established followed by the application of the modified SLFA on real-case multiobjective optimization problems in construction scheduling. The performance of SLFA was compared with that of the nondominated sorting genetic algorithm (NSGA II). The results showed that the developed new approach was superior in identifying optimal project planning solutions, which could essentially assist on-site power load-oriented schedule decision-making for construction teams.

Funder

General Research Fund

Publisher

Hindawi Limited

Subject

Civil and Structural Engineering

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