A Warfare Inspired Optimization Algorithm: The Find-Fix-Finish-Exploit-Analyze (F3EA) Metaheuristic Algorithm

Abstract

This paper introduces a new evolutionary algorithm for continuous optimization which mimics the targeting process of selecting objects or installations to be destroyed in warfare. The algorithm performs main steps of Find, Fix, Finish, Exploit and Analyze (F3EA) in an iterative manner. For the Find step, a new selection operator is introduced which mimics the object detection process followed by the radar devices. It is justified that how the Fix step can be modeled as a single variable optimization problem to scan the path between the two individuals to determine the precise location of a local optimum. During the Finish step, which is a mutation stage, it is assumed that an artificial missile is launched from the current position toward the position selected via the Find step. We use from the motion equations of Physics which govern the path traveled by the missile to generate the new solutions within the search space. The Exploit step tries to take over opportunities presented by the generated solution during the Finish step. Finally in the Analyze step, if the resultant solution of the Exploit step produces a better function value, it enters into the population or updates the global best solution. Performance of the proposed algorithm is tested on a collection of classic functions. Results demonstrate that the algorithm is very efficient and effective.