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Biogeography based optimization is a nature oriented concept. It extracts the idea of optimization from the way how species are distributed in various geographical areas. Various habitats are differentiated on the basis of habitat suitability index which determines strength of organisms in particular habitat. So habitat having highest habitat suitability index is known as best habitat. The same concept...
In this paper we have introduced the colonial multi-swarm, an algorithm with modular characteristics that can be augmented on several existing variants of Particle Swarm Optimization to alleviate the premature convergence problem. Colonial multi-swarm ensures a decent degree of exploration by administrating a number of parallel swarms. It uses a meta-level decision system that allows the particles...
As a special type of distributed evolutionary algorithms (DEAs), hierarchal distributed evolutionary algorithms (HDEAs) have been proposed for years. However, the number of their applications is very limited while simple DEAs are widely used in many field. In this paper, the advantage of HDEAs over simple DEAs is analyzed. Then a comparison experiment between a HDEA and a simple DEA is carried on...
By using differential evolution algorithm (DE) to solve multi-objective optimization problems, Pareto optimal solution migration based differential evolution for multi-objective optimization (PSDEMO) is proposed. The elitist strategy is adopted in the algorithm. Pareto non-dominated solutions found in the evolution operation are archived dynamically with the evolution process, and all the non-dominated...
This Paper presents a Biogeography-Based Optimization (BBO) algorithm to solve Optimal Power Flow (OPF) problems OPF) problems of a power system with generators having quadratic fuel cost characteristics. Different operational constraints such as generator capacity limits, power balance constraint, line flow limits, bus voltages, transformer tap settings and reactive power compensating device settings...
Biogeography-Based Optimization (BBO) is a new bio-inspired and population based optimization algorithm. The convergence of original BBO to the optimum value is slow. Intelligent Biogeography-Based Optimization (IBBO) technique is a hybrid version of BBO with Bacterial Foraging algorithm (BFA). In this paper, authors integrate the bacterial intelligence feature of BFA to decide the valid emigration...
To avoid the negative effect of guidance and to decrease congestion shifting caused because the drivers choose the optimum path simultaneously, more reasonable paths should be recommended, but there is no quick and effective algorithm to seek the k-shortest path. Genetic algorithm, characterized by overall optimization and potential parallel, is suitable for k-shortest path seeking. When the ordered...
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