Solving Fractional Programming Problems based on Swarm Intelligence

This paper presents a new approach to solveFractional Programming Problems (FPPs) based on twodifferent Swarm Intelligence (SI) algorithms. The twoalgorithms are: Particle Swarm Optimization, and FireflyAlgorithm. The two algorithms are tested using severalFPP benchmark examples and two selected industrialapplications. The test aims to prove the capability of the SIalgorithms to solve any type of FPPs. The solution resultsemploying the SI algorithms are compared with a numberof exact and metaheuristic solution methods used forhandling FPPs. Swarm Intelligence can be denoted as aneffective technique for solving linear or nonlinear, nondifferentiablefractional objective functions. Problems withan optimal solution at a finite point and an unboundedconstraint set, can be solved using the proposed approach.Numerical examples are given to show the feasibility,effectiveness, and robustness of the proposed algorithm.The results obtained using the two SI algorithms revealedthe superiority of the proposed technique among others incomputational time. A better accuracy was remarkablyobserved in the solution results of the industrial applicationproblems.