TITLE:
An Improved Ant Colony Optimization Algorithm for Construction Site Layout Problems
AUTHORS:
Gulben Calis, Orhan Yuksel
KEYWORDS:
Ant Colony Optimization, Construction Site Layout, Parameter Settings
JOURNAL NAME:
Journal of Building Construction and Planning Research,
Vol.3 No.4,
December
23,
2015
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.