Strength Pareto Evolutionary Algorithm based Multi-Objective Optimization for Shortest Path Routing Problem in Computer Networks | Science Publications

Journal of Computer Science

Subbaraj Potti¹  Chitra Chinnasamy¹ 

关键词: Shortest path routing problem;    evolutionary algorithm;    multi-objective optimization;    clustering;    strength pareto evolutionary algorithm;    Genetic Algorithm (GA);    Particle Swarm Optimization (PSO);    Non-dominated Sorting Genetic Algorithm (NSGA);    Quality of Service (QoS);    dynamic programming;    communication networks;   

DOI  :  10.3844/jcssp.2011.17.26

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

Problem statement: A new multi-objective approach, Strength Pareto EvolutionaryAlgorithm (SPEA), is presented in this paper to solve the shortest path routing problem. The routingproblem is formulated as a multi-objective mathematical programming problem which attempts tominimize both cost and delay objectives simultaneously. Approach: SPEA handles the shortest pathrouting problem as a true multi-objective optimization problem with competing and noncommensurableobjectives. Results: SPEA combines several features of previous multi-objective evolutionary algorithmsin a unique manner. SPEA stores nondominated solutions externally in another continuously-updatedpopulation and uses a hierarchical clustering algorithm to provide the decision maker with a manageablepareto-optimal set. SPEA is applied to a 20 node network as well as to large size networks ranging from50-200 nodes. Conclusion: The results demonstrate the capabilities of the proposed approach to generatetrue and well distributed pareto-optimal nondominated solutions.

【 授权许可】

Unknown