A Multiple Objective Ant - Q Algorithm for theDesign of Water Distribution

The diiculty in solving multiple objective optimization problems with traditional techniques, has urge researchers to use alternative approaches. Ant-Q algorithms have shown good results in the solution of combinatorial optimization problems, however little work has been done for multiple objective problems. This paper describes an Ant-Q algorithm called MOAQ, that can solve multiple objective optimization problems. MOAQ considers a family of agents for each objective function involved. Each family nds solutions that depend on solutions found by the rest of the families, creating a negotiation mechanism and nding compromise solutions for all the objectives involved. The compromise solutions are evaluated in the Pareto sense, assigning rewards to the non-dominated solutions tting all problems constraints, and punishments to the solutions violating any of them. 1 We compare and contrast the solutions obtained with MOAQ with the solutions obtained with two recently developed genetic algorithm approaches in two artiicial problems, demonstrating the ability of MOAQ to nd and maintain the Pareto frontier. Furthermore, it is shown how MOAQ is applied to a complex real-world problem; the design of irrigation water distribution networks, with very promising results.