This study explores the use of particle swarm optimization (PSO) and civilized swarm optimization (CSO) algorithms for design optimization of shell and tube heat exchangers from economic view point. Reliability and maintenance due to fouling are also taken into account. Two case studies are also presented and the results of optimization using PSO and CSO algorithms are compared with those obtained by using genetic algorithm (GA). The effect of variation of PSO and CSO algorithm parameters on convergence and optimum value of the objective function has also been presented.
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