Constrained economic optimization of shell-and-tube heat exchangers using a self-adaptive multi-population elitist-Jaya algorithm

[+] Author and Article Information
Venkata Rao

Dept. of Mech. Engg., Sardar Vallabhbhai National Institute of Technology, Surat-395 007, India

Ankit Saroj

Dept. of Mech. Engg., Sardar Vallabhbhai National Institute of Technology, Surat-395 007, India

1Corresponding author.

ASME doi:10.1115/1.4038737 History: Received June 12, 2017; Revised November 02, 2017


This paper explores the use of a self-adaptive multi-population elitist (SAMPE) Jaya algorithm for the economic optimization of shell-and-tube heat exchanger (STHE) design. Three different optimization problems of STHE are considered in this work. The same problems were earlier attempted by other researchers using genetic algorithm (GA), particle swarm optimization (PSO) algorithm, bio-geography based optimization (BBO), imperialist competitive algorithm (ICA), artificial bee colony (ABC), cuckoo-search algorithm (CSA), intelligence tuned harmony search (ITHS) and cohort intelligence (CI) algorithm. The Jaya algorithm is a newly developed algorithm and it does not have any algorithmic-specific parameters to be tuned except the common control parameters of number of iterations and population size. The search mechanism of the Jaya algorithm is upgraded in this paper by using the multi-population search scheme with the elitism. The SAMPE-Jaya algorithm is proposed in this paper to optimize the setup cost and operational cost of STHEs simultaneously. The performance of the proposed SAPME-Jaya algorithm is tested on four well known constrained, ten unconstrained standard benchmark problems and three STHE design optimization problems. The results of computational experiments proved the superiority of the proposed method over the latest reported methods used for the optimization of the same problems.

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