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Flower Pollination Algorithm with Linearly Varying Exploration: A Novel Approach for Continuous Function Optimization Problem
| Communications on Applied Electronics |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 7 - Number 16 |
| Year of Publication: 2018 |
| Authors: Mohammad Shafiul Alam, Sanonda Datta Gupta, Samiha Sara Prima, Nur-E-Asma Tabassum |
10.5120/cae2018652768
|
Mohammad Shafiul Alam, Sanonda Datta Gupta, Samiha Sara Prima, Nur-E-Asma Tabassum . Flower Pollination Algorithm with Linearly Varying Exploration: A Novel Approach for Continuous Function Optimization Problem. Communications on Applied Electronics. 7, 16 ( May 2018), 51-56. DOI=10.5120/cae2018652768
Abstract
The Flower Pollination Algorithm (FPA) a recently introduced bio–inspired algorithm based on the natural process of pollination of flowers. FPA has quickly drawn the attention of the research community due to its nature of both exploitation and exploration. In this paper we have introduced a novel variation in its mutation operation by linearly varying the value of its proximate probability parameter. We have evaluated the proposed algorithm on a number of benchmark problems and the experimental results are compared with the basic FPA. The empirical study indicates that the proposed FPA with variable exploration rate has better optimization performance than the basic FPA algorithm on most of the benchmark functions.
References
- Y. Xu, P. Fan and L. Yuan, "A Simple and Efficient Artificial Bee Colony Algorithm", Mathematical Problems in Engineering, vol. 2013, pp. 1-9, 2013.
- X. Yang and S. Deb, "Cuckoo search: recent advances and applications", Neural Computing and Applications, vol. 24, no. 1, pp. 169-174, 2013.
- X. Yang and X. He, "Bat algorithm: literature review and applications", International Journal of Bio-Inspired Computation, vol. 5, no. 3, p. 141, 2013.
- X. Yang, "Flower Pollination Algorithm for Global Optimization", Unconventional Computation and Natural Computation, pp. 240-249, 2012.
- X. Yang, M. Karamanoglu and X. He, "Multi-objective Flower Algorithm for Optimization", Procedia Computer Science, vol. 18, pp. 861-868, 2013.
- M. Abdel-Baset and I. Hezam, "A Hybrid Flower Pollination Algorithm for Engineering Optimization Problems", International Journal of Computer Applications, vol. 140, no. 12, pp. 10-23, 2016.
- O. Raouf, M. Baset and I. henawy, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", 2014.
- O. Abdel Raouf, I. El henawy and M. Abdel Baset, "A Novel Hybrid Flower Pollination Algorithm with Chaotic Harmony Search for Solving Sudoku Puzzles", International Journal of Modern Education and Computer Science, vol. 6, no. 3, pp. 38-44, 2014.
- B. Nozohour-leilabady and B. Fazelabdolabadi, "On the application of artificial bee colony (ABC) algorithm for optimization of well placements in fractured reservoirs; efficiency comparison with the particle swarm optimization (PSO) methodology", Petroleum, vol. 2, no. 1, pp. 79-89, 2016.
- P. N. Suganthan, N. Hansen, J. J. Liang, K. Deb, Y.-P. Chen, A. Auger and S. Tiwari, "Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization", Technical Report, Nanyang Technological University, Singapore, May 2005 AND KanGAL Report #2005005, IIT Kanpur, India.
- B. Liu, Q. Chen and Q. Zhang, J. J. Liang, P. N. Suganthan, B. Y. Qu, "Problem Definitions and Evaluation Criteria for Computationally Expensive Single Objective Numerical Optimization", Technical Report, Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou China and Technical Report, Nanyang Technological University, Singapore, December 2013.
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