A survey: optimization by evolutionary algorithms in refinery plants

because of the complexity of optimization problems in refinery plants due to the multi modality of the solution region of these problems with high dimensionally , optimization with conventional mathematical is not possible and necessity use of advanced tools optimizer was felt.evolutionary algorithms or population-based metaheuristic algorithms are a novel approaches use some mechanisms inspired by biological evolution: reproduciton, mutation, recombination, and selection and often perform well approximating solutions to all types of problems they ideally do not make any assumption about the underlying fitness landscape; this generality is shown by successes in engineering optimization problems. in fact ,EA is an emerging area in the field of optimization and researchers have developed various algorithms by modeling the behaviors of different swarm of animals and insects such as ants, termites , bees , birds, fishes. this paper will be presented a survey of novel approaches with evolutionary algorithms and their applications for optimization .

کلیدواژه ها:

evolutionary algorithm ، swarm intelligence algorithm ، ant colony ، bee colony ، honey bees mating optimizaiton ، refinery.