Author/Authors :
Abdel-Raouf، O نويسنده Associate Professor, Department of Operations Research, Faculty of Computers and Information, Menoufia University, Menoufia, Shebin-El-Kome, Egypt , , Abdel-Baset، M نويسنده Teaching Assistant, Department of Operations Research, Faculty of Computers and Informatics, Zagazig University, El-Zera Square, Zagazig, Sharqiyah, Egypt , , El-henawy، I نويسنده Professor, Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, El-Zera Square, Zagazig, Sharqiyah, Egypt ,
Abstract :
Abstract Global optimization methods play an important role to solve many real-world problems. Flower pollination algorithm (FP) is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new hybrid optimization method called hybrid flower pollination algorithm (FPPSO) is proposed. The method combines the standard flower pollination algorithm (FP) with the particle swarm optimization (PSO) algorithm to improve the searching accuracy. The FPPSO algorithm is used to solve constrained optimization problems. Experimental results showed that the accuracy of finding the best solution and convergence speed performance of the proposed algorithm is significantly better compared to those achieved by the existing algorithms
