Multi-Objective Optimization of Pumping Station Operation in Water Distribution Network Using ACO

فاقد چكيده فارسي

Ant Colony Optimization (ACO) is one of the recent evolutionary algorithms with high speed and efficient search comparing to other optimization methods. This research has two main objectives to optimize the operation of pumping station in water distribution network (WDN) by means of ACO. The first object is to minimize the cost of pumping energy consumption through the scheduling of pumping station and the second one is to maximize the reliability of pumping station. Due to the fact that in most of the multi-objective optimization problems in WDNs the objects are in conflict with each other, which means that improving one of the promises leads to the weakness of at least one of the other objectives, therefore, there is not only one specific solution. These solutions are presented by the pareto front. To find the best solutions in this algorithm, by means of crowding distance, it is tried to produce a set of solutions with uniform distribution and to converge the solutions to the true pareto front. By using multi-colony ant algorithm for multi-objective optimization that is modeled in Visual C++, the ability of this model is assessed to show the convergence and efficiency of this algorithm. Moreover, with the linkage of the proposed model to the EPANET2.0 simulator software, maximization of the reliability of pumping stations and minimization of the cost of pumping energy consumption are considered as a multi-objective optimization through a case study.