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Chaotic Evolutionary Programming for an Engineering Optimization Problem

doi: 10.3390/app11062717
The aim of the current paper is to present a mimetic algorithm called the chaotic evolutionary programming Powell’s pattern search (CEPPS) algorithm for the solution of the multi-fuel economic load dispatch problem. In the CEPPS algorithm, the exploration process is maintained by chaotic evolutionary programming, whereas exploitation is taken care off by a pattern search. The proposed CEPPS has two variants based on the Gauss map and the tent map. Seven generalized benchmark test functions and six cases of the multi-fuel economic load dispatch problem are considered for the performance analysis. It is observed from the analysis that the CEPPS solution procedure based on the tent map exhibits superiority to obtain an excellent solution and better convergence characteristics than traditional chaotic evolutionary programming. Further, the performance investigation for the considered economic load dispatch shows that the Gauss map CEPPS solution procedure performs better than the tent map based CEPPS to obtain the solution of the multi-fuel economic dispatch problem.
Technology, chaotic evolutionary programming, QH301-705.5, T, Physics, QC1-999, Powell’s pattern search, tent map, Engineering (General). Civil engineering (General), robustness test, Chemistry, Gauss map, TA1-2040, Biology (General), QD1-999
Technology, chaotic evolutionary programming, QH301-705.5, T, Physics, QC1-999, Powell’s pattern search, tent map, Engineering (General). Civil engineering (General), robustness test, Chemistry, Gauss map, TA1-2040, Biology (General), QD1-999
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).10 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
