Joaquín Izquierdo Sebastián

Agent Swarm Optimization: Exploding the search space

Agent Swarm Optimization is a framework that combines the use of evolutionary algorithms, data mining, modeling and other techniques to find the best compromises among objectives in complex decision problems. It has been applied mainly in engineering cases where using classic optimization algorithms would require undesired simplifications of the problem or the use of simulators for evaluating the objective functions. The flexibility of evolutionary algorithms makes possible to use them in practically any case. Nevertheless, in this paper we are presenting a complex problem where using “pure” evolutionary algorithms was not resulting in good solutions. A different situation appeared after using rules for reducing the search space and moving the evolutionary process toward zones with a higher probability of containing good solutions. The results of using rules is also presented in this paper for the case studied. Additionally, the paper explores the capacity of the algorithms to discover additional rules that can improve the search process and the way the evolutionary algorithms behave in problems where the expert knowledge to generate search rules is limited.

Water Distribution System Computer-Aided Design by Agent Swarm Optimization

Optimal design of water distribution systems (WDSs), including the sizing of components, quality control, reliability, renewal, and rehabilitation strategies, etc., is a complex problem in water engineering that requires robust methods of optimization. Classical methods of optimization are not well suited for analyzing highly dimensional, multimodal, nonlinear problems, especially given inaccurate, noisy, discrete, and complex data. Agent Swarm Optimization (ASO) is a novel paradigm that exploits swarm intelligence and borrows some ideas from multiagent-based systems. It is aimed at supporting decision-making processes by solving multiobjective optimization problems. ASO offers robustness through a framework where various population-based algorithms coexist. The ASO framework is described and used to solve the optimal design of WDS. The approach allows engineers to work in parallel with the computational algorithms to force the recruitment of new searching elements, thus contributing to the solution process with expert-based proposals.

Geographical Information Systems (GIS) Applied to Water Supply Systems (WSS)

In this paper, a general overview of a Geographical Information System is presented. First, a definition of some basic concepts about what a GIS is will be given, paying special attention to the topics related to the Georreferenced Databases. Afterwards, some general applications of the GIS technology to the Management of Water Supply Systems will be presented. Finally, a discussion on the potentiality of the GIS technology is developed.