@article {10.3844/jcssp.2011.17.26,
article_type = {journal},
title = {Strength Pareto Evolutionary Algorithm based Multi-Objective Optimization for Shortest Path Routing Problem in Computer Networks},
author = {Potti, Subbaraj and Chinnasamy, Chitra},
volume = {7},
number = {1},
year = {2010},
month = {Dec},
pages = {17-26},
doi = {10.3844/jcssp.2011.17.26},
url = {https://thescipub.com/abstract/jcssp.2011.17.26},
abstract = {Problem statement: A new multi-objective approach, Strength Pareto Evolutionary
Algorithm (SPEA), is presented in this paper to solve the shortest path routing problem. The routing
problem is formulated as a multi-objective mathematical programming problem which attempts to
minimize both cost and delay objectives simultaneously. Approach: SPEA handles the shortest path
routing problem as a true multi-objective optimization problem with competing and noncommensurable
objectives. Results: SPEA combines several features of previous multi-objective evolutionary algorithms
in a unique manner. SPEA stores nondominated solutions externally in another continuously-updated
population and uses a hierarchical clustering algorithm to provide the decision maker with a manageable
pareto-optimal set. SPEA is applied to a 20 node network as well as to large size networks ranging from
50-200 nodes. Conclusion: The results demonstrate the capabilities of the proposed approach to generate
true and well distributed pareto-optimal nondominated solutions.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}