Ant Colony Optimization for the Design of Water Distribution Systems

During the last decade, evolutionary methods such as genetic algorithms have been developed for the optimal design and operation of water distribution systems. More recently, ant colony optimization algorithms (ACOAs), which are evolutionary methods based on the foraging behavior of ants, been successfully applied to a number of benchmark combinatorial optimization problems. For example, when applied to the traveling salesman problem, ACOAs have been shown to outperform genetic algorithms. In this paper, a formulation is developed which enables ACOAs to be used for the optimal design of water distribution systems. This formulation is applied to a benchmark water distribution system optimization problem and the results are compared with those obtained using genetic algorithms. The findings of this study indicate that the performance of ACOAs is comparable with that of GAs for the case study considered. The GA performed slightly better in terms of finding the optimal solution from different starting positions in the search space, whereas the ACOA perfomed better in terms of the number of evaluations needed to reach the optimum.