A Novel Particle Swarm Optimization based Algorithm for Path Optimization in Embedded Systems

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概要

• 論文の詳細を見る

• This work presents a fast and memory efficient Particle Swarm Optimization (PSO) based algorithm for solving the multi-objective path optimization problem. The proposed algorithm uses innovative technique for particles' displacement which is based on exploring new sub-paths in the network in-order to improve the particles' positions. The proposed algorithm is implemented using C++ and executed on an ARM based embedded system. Its performance is compared with Non-dominated Sorting Algorithm-II (NSGA-II) and Simulated Annealing (SA). The results show that the proposed algorithm has found Pareto optimal solutions of quality equal to the NSGA-II and better than SA. The maximum number of paths which should be stored in the memory during optimization is about half of the NSGA-II. Therefore, it is suitable for implementation on embedded systems.

• 2012-02-23

著者

• Yoichi Shiraishi

  Department Of Production Science And Technology Gunma University

• Yoichi Shiraishi

  Department Of Production Science & Technology Gunma University Gunma Japan

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