This paper deals with the issue of reaching a target within an unknown search space. The target could be a human being, a bomb or any other object and the research space is composed of virtual robots, commonly known as agents that are continuously evolving together with the same purpose.
To that aim, we use the bio-inspired Particle Swarm Optimization (PSO) method that we extend to the Particle Swarm Optimization with dynamic ray (PSORM) algorithm.
The neighborhood is dynamically adjusted during the research process according to the value of fitness, which helps significantly to escape from local optimums. Despite the same variations we have made in some initial values such as population size and ray intensity, PSORM converges earlier. Our approach has the advantage to be completely distributed and of low-resources consumption.
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