Multi-objective optimization of two stage thermoelectric cooler using a modified teaching-learning-based optimization algorithm

被引：156

作者：

Rao, R. Venkata ^{[1
]}

Patel, Vivek ^{[1
]}

机构：

[1] SV Natl Inst Technol, Dept Mech Engn, Surat 395007, Gujarat, India

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2013年 / 26卷 / 01期

关键词：

Two stage thermoelectric cooler; Cooling capacity; Coefficient of performance; Thermoelectric modules; Teaching-learning-based optimization; HEAT-PUMP; OPTIMUM DESIGN; PERFORMANCE; CONFIGURATION; DEVICES; SYSTEM;

D O I：

10.1016/j.engappai.2012.02.016

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Teaching-learning-based optimization (TLBO) is a recently developed heuristic algorithm based on the natural phenomenon of teaching-learning process. In the present work, a modified version of the TLBO algorithm is introduced and applied for the multi-objective optimization of a two stage thermoelectric cooler (TEC). Two different arrangements of the thermoelectric cooler are considered for the optimization. Maximization of cooling capacity and coefficient of performance of the thermoelectric cooler are considered as the objective functions. An example is presented to demonstrate the effectiveness and accuracy of the proposed algorithm. The results of optimization obtained by using the modified TLBO are validated by comparing with those obtained by using the basic TLBO, genetic algorithm (GA), particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：430 / 445

页数：16

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