Genetic algorithm for optimization of energy systems: Solution uniqueness, accuracy, Pareto convergence and dimension reduction

• Main Authors: Ganjehkaviri, A., Mohd. Jaafar, M. N., Hosseini, S. E., Barzegaravval, H.
• Format: Article
• Published: Elsevier Ltd 2017
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/76115/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006867319&doi=10.1016%2fj.energy.2016.12.034&partnerID=40&md5=59b9ce75c0619e5f6c41a0327fd785ec

Genetic algorithm (GA) is widely accepted in energy systems optimization especially multi objective method. In multi objective method, a set of solutions called Pareto front is obtained. Due to random nature of GA, finding a unique and reproducible result is not an easy task for multi objective prob...