Jaya: An Advanced Optimization Algorithm and its Engineering Applications

verfasst von: Prof. Ravipudi Venkata Rao

Verlag: Springer International Publishing

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book introduces readers to the “Jaya” algorithm, an advanced optimization technique that can be applied to many physical and engineering systems. It describes the algorithm, discusses its differences with other advanced optimization techniques, and examines the applications of versions of the algorithm in mechanical, thermal, manufacturing, electrical, computer, civil and structural engineering.

In real complex optimization problems, the number of parameters to be optimized can be very large and their influence on the goal function can be very complicated and nonlinear in character. Such problems cannot be solved using classical methods and advanced optimization methods need to be applied. The Jaya algorithm is an algorithm-specific parameter-less algorithm that builds on other advanced optimization techniques. The application of Jaya in several engineering disciplines is critically assessed and its success compared with other complex optimization techniques such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), Artificial Bee Colony (ABC), and other recently developed algorithms.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract

This chapter presents an introduction to the single objective and multi-objective optimization problems and the optimization techniques to solve the same. The a priori and a posteriori approaches of solving the multi-objective optimization problems are explained. The importance of algorithm-specific parameter-less concept is emphasized.

Ravipudi Venkata Rao

Chapter 2. Jaya Optimization Algorithm and Its Variants

Abstract

This chapter presents the details of TLBO algorithm, NSTLBO algorithm, Jaya algorithm and its variants named as Self-Adaptive Jaya, Quasi-Oppositional Jaya, Self-Adaptive Multi-Population Jaya, Self-Adaptive Multi-Population Elitist Jaya, Chaos Jaya, Multi-Objective Jaya, and Multi-Objective Quasi-Oppositional Jaya. Suitable examples are included to demonstrate the working of Jaya algorithm and its variants for the unconstrained and constrained single and multi-objective optimization problems. Three performance measures of coverage, spacing and hypervolume are also described to assess the performance of the multi-objective optimization algorithms.

Ravipudi Venkata Rao

Chapter 3. Application of Jaya Algorithm and Its Variants on Constrained and Unconstrained Benchmark Functions

Abstract

This chapter presents the results of application of Jaya algorithm and its variants like SAMP-Jaya and SAMPE-Jaya algorithms on 15 unconstrained benchmark functions given in CEC 2015 as well as 15 other unconstrained functions and 5 constrained benchmark functions. The results are compared with those given by the other well known optimization algorithms. The results have shown the satisfactory performance of Jaya algorithm and its variants for the considered CEC 2015 benchmark functions and the other constrained and unconstrained optimization problems. The statistical tests have also supported the performance supremacy of the variants of the Jaya algorithm.

Ravipudi Venkata Rao

Chapter 4. Single- and Multi-objective Design Optimization of Heat Exchangers Using Jaya Algorithm and Its Variants

Abstract

This chapter presents design optimization case studies of shell-and-tube and plate-fin heat exchangers. The single objective and multi-objective design optimization case studies are solved by the Jaya algorithm and its variants such as self-adaptive Jaya, SAMP-Jaya and SAMPE-Jaya. The results of application of Jaya algorithm and its variants are compared with those of the other state-of-the-art optimization algorithms and the performance supremacy of the Jaya algorithm and its variants is established.

Ravipudi Venkata Rao

Chapter 5. Single- and Multi-objective Design Optimization of Heat Pipes and Heat Sinks Using Jaya Algorithm and Its Variants

Abstract

This chapter presents the application of Jaya algorithm and its variants for the single objective as well as multi-objective design optimization of heat pipes and heat sinks. Design of heat pipes and heat sinks involves a number of geometric and physical parameters with high complexity and the design processes are mostly based on trial and error. General design approaches become tedious and time consuming and these processes do not guarantee the achievement of an optimal design. Therefore, meta-heuristic based computational methods are preferred. This chapter presents the results of application of Jaya algorithm and its variants such as self-adaptive Jaya algorithm, SAMP-Jaya algorithm and SAMPE-Jaya algorithm to the design optimization problems of heat pipes and heat sinks. The results are found better than those obtained by other optimization techniques such as TLBO, Grenade Explosion Method (GEM), Niched Pareto Genetic Algorithm (NPGA), Generalized External optimization (GEO) and a hybrid multi-objective evolutionary algorithm.

Ravipudi Venkata Rao

Chapter 6. Multi-objective Design Optimization of Ice Thermal Energy Storage System Using Jaya Algorithm and Its Variants

Abstract

This chapter presents the details of the performance optimization of an Ice Thermal Energy Storage (ITES) system carried out using TLBO algorithm, Jaya and self-adaptive Jaya algorithms. The results achieved by using Jaya and self-adaptive Jaya algorithms are compared with those obtained by using the GA and TLBO techniques for ITES system with phase change material (PCM). In ITES system, two objective functions including exergy efficiency (to be maximized) and total cost rate (to be minimized) of the whole system are considered. The Jaya and self-adaptive Jaya algorithms are proved superior to GA and TLBO optimization algorithms in terms of robustness of the results. The self-adaptive Jaya takes less computational time and the function evaluations as compared to the other algorithms.

Ravipudi Venkata Rao

Chapter 7. Single- and Multi-objective Optimization of Traditional and Modern Machining Processes Using Jaya Algorithm and Its Variants

Abstract

This chapter describes the formulation of process parameters optimization models for traditional machining processes of turning, surface grinding and modern machining processes of wire electric discharge machining (wire EDM), electro-discharge machining (EDM), micro-electric discharge machining, electro-chemical machining (ECM), abrasive waterjet machining (AWJM), focused ion beam (FIB) micro-milling, laser cutting and plasma arc machining. The TLBO and NSTLBO algorithms, Jaya algorithm and its variants such as Quasi-oppositional (QO) Jaya, multi-objective (MO) Jaya, and multi-objective quasi-oppositional (MOQO) Jaya are applied to solve the single and multi-objective optimization problems of the selected traditional and modern machining processes. The results are found better as compared to those given by the other advanced optimization algorithms.

Ravipudi Venkata Rao

Chapter 8. Single- and Multi-objective Optimization of Nano-finishing Processes Using Jaya Algorithm and Its Variants

Abstract

This chapter describes the formulation of process parameters optimization models for nano-finishing processes of rotational magnetorheological abrasive flow finishing, magnetic abrasive finishing, magnetorheological fluid based finishing, and abrasive flow machining. The application of TLBO and NSTLBO algorithms, Jaya algorithm and its variants such as Quasi-oppositional (QO) Jaya and multi-objective (MO) Jaya is made to solve the single and multi-objective optimization problems of the selected nano-finishing processes. The results of Jaya algorithm and its variants are found better as compared to those given by the other approaches.

Ravipudi Venkata Rao

Chapter 9. Single- and Multi-objective Optimization of Casting Processes Using Jaya Algorithm and Its Variants

Abstract

In the case of casting processes, the effectiveness of Jaya and QO-Jaya algorithms is tested on optimization problems of squeeze casting process, continuous casting process, pressure die casting process and green sand casting process. The results of Jaya and QO-Jaya algorithms are compared with the results of GA, PSO, SA, TLBO algorithms and Taguchi method used by the previous researchers on the basis of objective function value, convergence speed and computational time. The results of Jaya and QO-Jaya algorithm are found better.

Ravipudi Venkata Rao

Chapter 10. Applications of Jaya Algorithm and Its Modified Versions to Different Disciplines of Engineering and Sciences

Abstract

After its introduction in 2016 by Rao (Int J Ind Eng Comput 7:19–34, 2016), the Jaya algorithm is quickly finding a large number of applications in different fields of engineering and science. This chapter presents an overview of the applications of the Jaya algorithm and its modifications published in reputed international journals since 2016 till March 2018.

Ravipudi Venkata Rao

Backmatter

Titel: Jaya: An Advanced Optimization Algorithm and its Engineering Applications
verfasst von: Prof. Ravipudi Venkata Rao
Verlag: Springer International Publishing
Electronic ISBN: 978-3-319-78922-4
Print ISBN: 978-3-319-78921-7
DOI: https://doi.org/10.1007/978-3-319-78922-4