Biogeography-Based Optimization: Synergies with Evolutionary Strategies, Immigration Refusal, and Kalman Filters
Date of Award
Electrical and Computer Engineering
Biogeography -- Mathematical models, Mathematical optimization, Traveling-salesman problem, Genetic algorithms, Kalman filtering
Biogeography-based optimization (BBO) is a recently developed heuristic algorithm which has shown impressive performance on many well known benchmarks. The aim of this thesis is to modify BBO in different ways. First, in order to improve BBO, this thesis incorporates distinctive techniques from other successful heuristic algorithms into BBO. The techniques from evolutionary strategy (ES) are used for BBO modification. Second, the traveling salesman problem (TSP) is a widely used benchmark in heuristic algorithms, and it is considered as a standard benchmark in heuristic computations. Therefore the main task in this part of the thesis is to modify BBO to solve the TSP, then to make a comparison with genetic algorithms (GAs). Third, most heuristic algorithms are designed for noiseless environments. Therefore, BBO is modified to operate in a noisy environment with the aid of a Kalman filter. This involves probability calculations, therefore BBO can choose the best option in its immigration step
Du, Dawei, "Biogeography-Based Optimization: Synergies with Evolutionary Strategies, Immigration Refusal, and Kalman Filters" (2009). ETD Archive. 680.