APPLICATION OF PARALLEL GENETIC ALGORITHM IN DAILY LIFE Adib Hafifi Jamal Abdul Nasir Alamir #1, Mohamed Faidz Mohamed Said #2 # Universiti Teknologi MARA 70300 Seremban, Negeri Sembilan, MALAYSIA 1 adibhafifi9393@gmail.com 2 faidzms@ieee.org Abstract—Genetic algorithm was used to find the solution to problems by Darwinian Evolution and the same applies to Parallel Genetic Algorithm (PGA) which was created by John Holland. Genetic algorithms are the best search methods that rely on the principles of natural selection and genetics. The objective of this paper is to show where the Parallel Genetic Algorithm had been applied in our life. A model is used to optimize bus route headway which aims to locate an adequate harmony between passenger and operator costs and it is called as the optimal of service quality and the minimization of operational costs. The combination of Graphics Processing Unit with Parallel Genetic Algorithm to generate daily activity plans is the solution for the problem. A methodology is proposed in terms of yard crane scheduling as well as a dynamic Hierarchical Parallel Genetic Algorithm using Grid Computing. Today, Parallel Genetic Algorithm has been used widely due to the powerful search it provides and it is also the hard programs that control many parameters. Keywords: Parallel Genetic Algorithm, GPU REFERENCES [1] E. Cantú-Paz and D. E. Goldberg, "Efficient parallel genetic algorithms: theory and practice," Computer Methods in Applied Mechanics and Engineering, vol. 186, pp. 221-238, 6/9/ 2000. [2] T. H.Kaiser, "Title," unpublished. [3] J. Stender, Parallel genetic algorithms: theory and applications vol. 14: IOS press, 1993. [4] E. Cantú-Paz, "A survey of parallel genetic algorithms," Calculateurs paralleles, reseaux et systems repartis, vol. 10, pp. 141-171, 1998. [5] R. Salomon, "Re-evaluating genetic algorithm performance under coordinate rotation of benchmark functions. A survey of some theoretical and practical aspects of genetic algorithms," BioSystems, vol. 39, pp. 263-278, 1996. [6] J.-M. Renders and S. P. Flasse, "Hybrid methods using genetic algorithms for global optimization," IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 26, pp. 243-258, 1996. [7] B. Yu, Z. Yang, X. Sun, B. Yao, Q. Zeng, and E. Jeppesen, "Parallel genetic algorithm in bus route headway optimization," Applied Soft Computing, vol. 11, pp. 5081-5091, 2011. [8] K. Wang and Z. Shen, "A GPU-Based Parallel Genetic Algorithm for Generating Daily Activity Plans," IEEE Transactions on Intelligent Transportation Systems, vol. 13, pp. 1474-1480, 2012. [9] V. Roberge, M. Tarbouchi, and G. Labonte, "Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning," IEEE Transactions on Industrial Informatics, vol. 9, pp. 132-141, 2013. [10] J. He, D. Chang, W. Mi, and W. Yan, "A hybrid parallel genetic algorithm for yard crane scheduling," Transportation Research Part E: Logistics and Transportation Review, vol. 46, pp. 136-155, 2010. [11] D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff, and B.-S. Lee, "Efficient Hierarchical Parallel Genetic Algorithms using Grid computing," Future Generation Computer Systems, vol. 23, pp. 658-670, 2007.