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Conjoining MMAS to GA to Solve Construction Site Layout Planning Problem |
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| Authors: | Ka-Chi Lam Xin Ning Mike Chun-Kit Lam |
| Affiliation: | 1Associate Professor, Dept. of Building and Construction, City Univ. of Hong Kong, 83 Tat Chee Ave., Kowloon, Hong Kong SAR, China (corresponding author). E-mail: bckclam@cityu.edu.hk 2Lecturer, School of Investment and Construction Management, Dongbei Univ. of Finance and Economics, Dalian, China. E-mail: ningxinsummer@yahoo.com.cn 3Instructor, Dept. of Building and Construction, City Univ. of Hong Kong, 83 Tat Chee Ave., Kowloon, Hong Kong SAR, China. E-mail: chkilam@cityu.edu.hk |
| Abstract: | An optimal construction site layout planning (CSLP) is vital for project management. It can reduce the transportation flows and thus the costs of a project. Genetic algorithm (GA) is the most used algorithm to solve site layout problems, but randomly generated initial population in GA will decrease solution quality. Max-min ant system (MMAS) can offer a better initial population than the randomly generated initial population at the beginning of GA. In this study, a modified GA (MMAS-GA) formed by conjoining MMAS to the step of initialization of GA is proposed to solve CSLP problems. In order to reveal the computational capability of MMAS-GA to solve CSLP problems, the results of MMAS-GA and traditional GA are compared by solving an equal-area CSLP problem. The results showed that the proposed MMAS-GA algorithm provided a better optimal solution under the objective function of minimizing the transportation flows between the site facilities. The proposed MMAS-GA algorithm could assist project managers and planners to design optimal construction site layout, and thus to reduce construction costs. |
| Keywords: | Construction sites Algorithms Optimization Construction management |