An Improved Ant Colony Optimization Algorithm for Construction Site Layout Problems

Gulben Calis; Orhan Yuksel

doi:10.4236/jbcpr.2015.34022

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JBCPR> Vol.3 No.4, December 2015

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An Improved Ant Colony Optimization Algorithm for Construction Site Layout Problems

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DOI: 10.4236/jbcpr.2015.34022 3,450 Downloads 4,381 Views Citations

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Gulben Calis, Orhan Yuksel

Affiliation(s)

Department of Civil Engineering, Ege University, Izmir, Turkey.

ABSTRACT

Meta-heuristic algorithms proved to find optimal solutions for combinatorial problems in many domains. Nevertheless, the efficiency of these algorithms highly depends on their parameter settings. In fact, finding appropriate settings of the algorithm’s parameters is considered to be a nontrivial task and is usually set manually to values that are known to give reasonable performance. In this paper, Ant Colony Optimization with Parametric Analysis (ACO-PA) is developed to overcome this drawback. The main feature of the ACO-PA is the ability of deciding the appropriate parameter values within the predefined parameter variations. Besides, a new approach which enables the pheromone information value to be proportional to the heuristic information value is introduced. The effectiveness of the proposed algorithm is investigated through the application of the algorithm to the construction site layout problems taken from the state-of-art. Results show that the ACO-PA can reduce transportation cost up to 16.8% compared to the site layouts generated by Genetic Algorithms and basic ACO. Moreover, the effects of parameter settings on the generated solutions are investigated.

KEYWORDS

Ant Colony Optimization, Construction Site Layout, Parameter Settings

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Calis, G. and Yuksel, O. (2015) An Improved Ant Colony Optimization Algorithm for Construction Site Layout Problems. Journal of Building Construction and Planning Research, 3, 221-232. doi: 10.4236/jbcpr.2015.34022.

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