ant colony optimization algorithm

Optimal operation of multi-reservoir systems is amongst the important problems in the field of water engineering which cannot be easily solved. Nowadays, water engineering experts are using Meta-heuristic algorithms to solve this problem due to the computational capabilities of these algorithms. Ant Colony Optimization algorithm is one of the algorithms which is based on foraging behavior of real ants. In this research, the capability of four different ant colony optimization algorithms, Ant System, Elitist Ant System, Ranked Ant system, and Max-Min Ant System has been tested to solve the four- and ten-reservoir benchmark systems. For each algorithm two different formulations are proposed; in the first formulation reservoir releases and in the second formulation reservoir storages are considered as decision variables of the problem. The results showed that the Ant Colony Optimization algorithm is a competent algorithm to solve Multi-reservoir system operation optimization problem. The Max-Min Ant System is also assessed as superior to other algorithms for such problems.

Deliberate chemical contaminant injection is one of the most important dangers which threatens urban water distribution networks. Decisions made following the detection of such contaminant attacks are affected by complicated conditions. A variety of optimal operational measures and strategies must be adopted to safeguard the public health which may include isolation of the contaminated area through valve operations for pollution containment, public alarms, and flushing of the polluted water out of the system through hydrants or pumps. In this study, consequence management of chemical intrusions using the above strategies is investigated with two main minimizing the number of polluted nodes and minimizing the operational activities while minimizing "the recovery time of the network to normal conditions" is also considered as a novel objective. The problem is treated as both a single- and a multi-objective optimization problem in which the Ant Colony Optimization Algorithm is used for the first time. One of the most important achievements of this study is the substantial role of pumps in consequence management of such attacks.

In this paper a heuristic method with ad-hoc engineering concept is proposed for design optimization of integrated wastewater treatment and sanitary sewer network using ant colony optimization algorithm. The optimal design of integrated wastewater treatment and sewer network requires that the wastewater treatment location، layout and size of sewer network are optimally determined. The problem of finding the optimal design of integrated wastewater treatment and sanitary sewer network is an expensive task that should be formulated as an optimization problem if an optimal least cost design is required. This problem is a highly constrained Mixed-Integer Nonlinear Programming (MINLP) problem presenting a challenge even to conventional methods. In this paper an efficient heuristic method with ad-hoc engineering concept using ant colony optimization algorithm is proposed and used to solve hypothetical test example and the results are presented and compared with those of obtained with using genetic algorithm. The results indicate the effectiveness and efficiency of the proposed method to optimally solve the problem of optimal design of integrated wastewater treatment and sewer network.