Using Self-Configurable Particle Swarm Optimization for Allocation Position of Rescue Robots

Abstract

Man has always tried to make new systems, which can do his difficult tasks. Manage and control of such new complex systems is new challenge in our life. Today, one solution to deal with this challenge is using advantage of features of autonomy. It means that instead of managing and controlling the entire system, each component or at least part of the system can manage or control itself even in unpredictable situations. In this paper, we proposed a new algorithm, is named “self-configurable particle swarm optimization algorithm (SCPSO)”. This method can control a system without outside observers in decentralize fashion. Each particle can makes decision to find optimum position for itself even when there is not enough information from whole system. By this method, particles can work autonomously even in unpredictable situations. We examine our proposed algorithm in both static and dynamic environments. This algorithm is a good method for using in disaster management or crisis management. Results show this method is a successful, especially in communication less environments.