Engineering Nature-Inspired Heuristics for the Open Shortest Path First Weight Setting Problem

Abstract

In the thesis of “Mohammed Aijaz Mohiuddin”, Engineering Nature-Inspired Heuristics for the Open Shortest Path First Weight Setting Problem, nature inspired heuristics were developed. Besides the existing two objectives, namely maximum utilization and the number of congested links, a third objective namely the number of unused links was used to formulate the fuzzy based objective function for the OSPFWS problem. The idea was to make use unused network links if any. Furthermore, a hybrid fuzzy based evolutionary Particle Swarm Optimization (FEPSO) algorithm was designed that harnessed evolutionary intelligence along with swarm intelligence. The proposed FEPSO algorithm was tested on different size test cases and its performance was mutually compared with other algorithms namely Simulated Annealing, Simulated Evolution, Particle Swarm Optimization, Weighted Aggregation Particle Swarm Optimization, Pareto-dominance Particle Swarm Optimization and Non-dominating Sorting Genetic Algorithm. Obtained results suggested the better performance of FEPSO among other algorithms over majority of test cases.