Source Detection of Oil Spill using Modified Glowworm Swarm optimization

Abstract

Crude oil has become very important source of energy. It is used by industries for supplying energy, providing fuel for vehicles etc. It is carried by submarines pipelines, ships and tankers to industries. Due to carelessness of human beings or natural disaster oil gets leaked from pipelines or ships and goes into the ocean. The oil in the ocean imposes danger to marine lives. In this paper, the source of oil spill is detected through swarm robots along with the use of swarm intelligence algorithm i.e. Modified Glowworm Swarm optimization(MGSO) Algorithm. In this algorithm, we use variant step size on the static function profile (instead of fixed step size) to speed up the convergence rate. The result gives better performance if number of iteration and number of s-bots get decreased. The comparison of analysis is done by using some benchmark function and evaluation measures on the basis of PCR(Peak Captured Rate). The maximum number of sources of oil spill is identified. In future work, this algorithm will work on real time for measurement of wind effect and also formed boundary of oil spill for cleaning process through swarm-bots.