Solving Fractional Programming Problems based on Swarm Intelligence

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• 作者：Osama Abdel Raouf (1)
  Ibrahim M. Hezam (1) (2)
  
• 关键词：Swarm intelligence ; Particle swarm optimization ; Firefly algorithm ; Fractional programming
• 刊名：Journal of Industrial Engineering International
• 出版年：2014
• 出版时间：June 2014
• 年：2014
• 卷：10
• 期：2
• 全文大小：1,178 KB
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• 作者单位：Osama Abdel Raouf (1)
  Ibrahim M. Hezam (1) (2)
  
  1. Operations Research and DSS Department, Menofia University, Shebien El-koum, Menofia聽, 32511, Egypt
  2. Department of Mathematics and computer, Faculty of Education, Ibb University, Ibb city, Yemen
  
• ISSN：2251-712X

文摘

This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to solve any type of FPPs. The solution results employing the SI algorithms are compared with a number of exact and metaheuristic solution methods used for handling FPPs. Swarm Intelligence can be denoted as an effective technique for solving linear or nonlinear, non-differentiable fractional objective functions. Problems with an optimal solution at a finite point and an unbounded constraint 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 revealed the superiority of the proposed technique among others in computational time. A better accuracy was remarkably observed in the solution results of the industrial application problems.