Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms

DOI10.1016/j.ins.2010.12.006zbMath1216.68252OpenAlexW2102227845MaRDI QIDQ543817

Dan Simon, Mehmet Ergezer, Dawei Du, Rick Rarick

Publication date: 17 June 2011

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://engagedscholarship.csuohio.edu/cgi/viewcontent.cgi?article=1010&context=enece_facpub

zbMATH Keywords

genetic algorithmMarkov modelevolutionary algorithmbenchmarkbiogeography-based optimizationglobal uniform recombination

Mathematics Subject Classification ID

Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (14)

Biogeography-based optimization for optimal job scheduling in cloud computing ⋮ An analysis of why cuckoo search does not bring any novel ideas to optimization ⋮ A novel generalized oppositional biogeography-based optimization algorithm: application to peak to average power ratio reduction in OFDM systems ⋮ Enhancing the performance of biogeography-based optimization using polyphyletic migration operator and orthogonal learning ⋮ Exposing the grey wolf, moth‐flame, whale, firefly, bat, and antlion algorithms: six misleading optimization techniques inspired by bestial metaphors ⋮ Mean-based Borda count for paradox-free comparisons of optimization algorithms ⋮ On the convergence of biogeography-based optimization for binary problems ⋮ Complex system optimization using biogeography-based optimization ⋮ Biogeography Based Optimization for Water Pump Switching Problem ⋮ Enhancing the performance of biogeography-based optimization using multitopology and quantitative orthogonal learning ⋮ Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms ⋮ Enhancing artificial bee colony algorithm using more information-based search equations ⋮ Hybrid evolutionary fuzzy learning scheme in the applications of traveling salesman problems ⋮ Novel biogeography-based optimization algorithm with hybrid migration and global-best Gaussian mutation

Uses Software

• TSPLIB
• Genocop

Cites Work

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• Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms
• Knowledge incorporation in evolutionary computation
• Modeling genetic algorithms with Markov chains.
• Simple explanation of the no-free-lunch theorem and its implications
• Genetic algorithms: Principles and perpectives. A guide to GA theory
• Advances in evolutionary computing. Theory and applications
• Solving the one-dimensional bin packing problem with a weight annealing heuristic
• Convergence of an annealing algorithm
• A graph coloring algorithm for large scheduling problems

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