Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Theoretical Computer Science - Special issue on evolutionary computation
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
Population distributions in biogeography-based optimization algorithms with elitism
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Biogeography-based optimization and the solution of the power flow problem
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Oppositional biogeography-based optimization
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Biogeography-based optimization of neuro-fuzzy system parameters for diagnosis of cardiac disease
Proceedings of the 12th annual conference on Genetic and evolutionary computation
An analysis of the equilibrium of migration models for biogeography-based optimization
Information Sciences: an International Journal
Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms
Information Sciences: an International Journal
A probabilistic analysis of a simplified biogeography-based optimization algorithm
Evolutionary Computation
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
A Multiobjective Optimization-Based Evolutionary Algorithm for Constrained Optimization
IEEE Transactions on Evolutionary Computation
Biogeography-Based Optimization
IEEE Transactions on Evolutionary Computation
Markov Models for Biogeography-Based Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multi-objective biogeography based optimization for optimal PMU placement
Applied Soft Computing
Accelerated biogeography-based optimization with neighborhood search for optimization
Applied Soft Computing
Emergency railway wagon scheduling by hybrid biogeography-based optimization
Computers and Operations Research
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Abstract: We derive a dynamic system model for biogeography-based optimization (BBO) that is asymptotically exact as the population size approaches infinity. The states of the dynamic system are equal to the proportion of each individual in the population; therefore, the dimension of the dynamic system is equal to the search space cardinality of the optimization problem. The dynamic system model allows us to derive the proportion of each individual in the population for a given optimization problem using theory rather than simulation. The results of the dynamic system model are more precise than simulation, especially for individuals that are very unlikely to occur in the population. Since BBO is a generalization of a certain type of genetic algorithm with global uniform recombination (GAGUR), an additional contribution of our work is a dynamic system model for GAGUR. We verify our dynamic system models with simulation results. We also use the models to compare BBO, GAGUR, and a GA with single-point crossover (GASP) for some simple problems. We see that with small mutation rates, as are typically used in real-world problems, BBO generally results in better optimization results than GAs for the problems that we investigate.