An immune plasma algorithm based approach for UCAV path planning

Abstract

Immune Plasma algorithm for short IPA is one of the most recent meta-heuristics and differs when the speciality of the process tried to be modeled is considered. The competitive performance of the IPA on different numerical optimization or engineering problems gave inspiration for the studies related with the specializing or porting IPA to more complex real world problems. In this study, IPA was ported in order to solve unmanned combat aerial vehicle (UCAV) path planning problem and its capabilities were investigated in detail by assigning different values to the population size, number of donors-receivers and using challenging battlefield scenarios. The results found by the IPA were also compared with the results obtained by a set of well-known meta-heuristic algorithms. The comparative studies informed that IPA is capable of finding more robust path or paths for the UCAV operating on a battlefield and outperforms other executed algorithms for almost all the test scenarios.