Heat transfer search (HTS): a novel optimization algorithm

Patel, Vivek; Savsani, Vimal

doi:10.1016/j.ins.2015.06.044

Cited by 232 publications

(99 citation statements)

References 47 publications

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“…It is a metaheuristic optimization algorithm proposed by Patel and Savsani in 2015 [22]. HTS is inspired by the fundamental thermodynamics laws, where the searching agents emulate systems interacting with other systems, and their surrounding environment exchanging energy.…”

Section: Heat Transfer Search (Hts)mentioning

confidence: 99%

Global optimization algorithms applied in a parameter estimation strategy

Matajira-Rueda¹,

Duarte²,

Cervantes³

et al. 2018

revuin

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Vol. 17, no. 1, pp. 233-242, enero-junio 2018 Revista UIS Ingenierías ABSTRACTThis article presents a comparative study using two global optimization algorithms, Electromagnetic Field Optimization (EFO) and Heat Transfer Search (HTS). These techniques are efficient alternatives when classical methods find limitations to solve real problems. To verify methods performance, the rectangular microchannel heat sink design was implemented formulating the respective Inverse Heat Transfer Problem (IHTP). Experimental results were competitively compared with the traditional Levenberg-Marquardt (LM) outcomes. Moreover, global algorithms achieved estimations with errors lower than 5%, and they converged at least three times faster than LM. KEYWORDS:Electromagnetic field optimization (EFO), entropy generation minimization (EGM), heat transfer search (HTS), inverse heat transfer problem (IHTP), Levenberg-Marquardt method (LM), ordinary least squares norm (OLSN). RESUMENEste artículo presenta un estudio comparativo utilizando dos algoritmos de optimización global, el de Optimización por Campo Electromagnético (EFO) y el de Búsqueda por Transferencia de Calor (HTS). Estas técnicas alternativas son eficientes cuando los métodos clásicos encuentran limitaciones para resolver problemas reales. Para verificar el desempeño de los métodos, se implementó el diseño de un disipador de calor de microcanales rectangulares formulando el respectivo problema inverso de transferencia de calor (IHTP). Los resultados experimentales se compararon competitivamente con los resultados tradicionales de Levenberg-Marquardt (LM). Además, los algoritmos globales lograron estimaciones con errores inferiores al 5%, y convergieron al menos tres veces más rápido que LM.

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Section: Heat Transfer Search (Hts)mentioning

confidence: 99%

Global optimization algorithms applied in a parameter estimation strategy

Matajira-Rueda¹,

Duarte²,

Cervantes³

et al. 2018

revuin

View full text Add to dashboard Cite

show abstract

“…The detailed information about the thermal equilibrium and heat transfer can be found in the study of Patel and Savsani (2015) and other sources (Hollman, 2010;Çengel, 2008;von Böckh and Wetzel, 2012). Therefore, the same definitions and equations will not be repeated here for the sake of brevity.…”

Section: The Heat Transfer Search Algorithmmentioning

confidence: 99%

“…The laws of thermodynamics and heat transfer have been incorporated by Patel and Savsani (2015) into the Heat Transfer Search (HTS) metaheuristic optimization algorithm, developed for constrained optimization problems. The HTS algorithm consists of three phases called as 'conduction phase', 'radiation phase' and 'convection phase'.…”

Section: The Heat Transfer Search Algorithmmentioning

confidence: 99%

“…The temperature dependent behaviour of conductance is accounted for by the variable Rn which can take any value between 0 and 0.3333 at the beginning of each generation in the conduction phase. Moreover, to exploit the search space, this random variable is modelled by squaring its value so to carry out a fine search (Patel and Savsani, 2015).…”

Section: Latin American Journal Of Solids and Structures 14 (2017) 37mentioning

confidence: 99%

“…A novel metaheuristic search method called heat transfer search (HTS) has been recently developed by Patel and Savsani (2015) for solving optimization problems. HTS simulates the course of action followed by a system to reach thermal equilibrium.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Heat Transfer Search Algorithm for Sizing Optimization of Truss Structures

Degertekin

Lamberti

Hayalioglu

2017

Lat. Am. j. solids struct.

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Heat transfer search (HTS) is a novel metaheuristic optimization algorithm that simulates the laws of thermodynamics and heat transfer. In this study, the HTS algorithm is adapted to truss structure optimization. Sizing optimization searches for the minimum weight of a structure subject to stress and displacement constraints. Three truss structures often taken as benchmarks in the optimization literature are selected here in order to verify the efficiency and robustness of the HTS algorithm. Optimization results indicate that HTS can obtain better designs (i.e. lighter trusses) than most of the state-of-the-art metaheuristic optimizers. The convergence behaviour of HTS also is as good as the other algorithms.

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Social optimization algorithm with application to economic dispatch problem

Karimi

Khandani

2020

Int Trans Electr Energ Syst

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Summary In this paper, a new population‐based meta‐heuristic algorithm called Social Optimization Algorithm (SOA) is proposed. This algorithm has been inspired by the social behavior of human‐beings, and mimics an ideal justly‐established society where the two principles of justice, that is, equality of opportunity and community principles are meticulously followed. Reaching goals in such a society is optimally achieved. Although a real fully‐just society does not exist in the real world, we implement the principles in such ideal societies through simulations to introduce our new optimization algorithm. The advantage of the proposed method is that it does not have any algorithm‐specified parameters to be set. This is a great merit compared to similar meta‐heuristics. The algorithm has been simulated on 23 well‐known test functions, and the results have been compared with those produced by Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA) and Differential Evolution (DE). In 57% of the 23 cases SOA yields superior results. The algorithm has also been tested on five other benchmark functions to be compared with Teaching‐Learning‐Based Optimization (TLBO) and Artificial Bee Colony (ABC).The results provide evidence for efficient performance with superior solution quality of the proposed algorithm in solving benchmark problems. To further illustrate the effectiveness of the proposed algorithm, it has been tested on the Economic Dispatch problem as a real‐world constrained optimization problem. The results have been compared with Biogeography‐Based Optimizer (BBO), Harmony Search (HS) and PSO. The results show that the SOA is able to produce very competitive results compared to other well‐known meta‐heuristic algorithms. Meta‐heuristic, SOA, Economic Dispatch.

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Heat transfer search (HTS): a novel optimization algorithm

Cited by 232 publications

References 47 publications

Global optimization algorithms applied in a parameter estimation strategy

Global optimization algorithms applied in a parameter estimation strategy

Heat Transfer Search Algorithm for Sizing Optimization of Truss Structures

Social optimization algorithm with application to economic dispatch problem

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