A CRITICAL STUDY ON TEN NON-TRADITIONAL OPTIMIZATION METHODS IN SOLVING ENGINEERING PROBLEMS

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Title:	A CRITICAL STUDY ON TEN NON-TRADITIONAL OPTIMIZATION METHODS IN SOLVING ENGINEERING PROBLEMS
Authors:	J, Rejula Mercy S, Elizabeth Amudhini Stephen
Keywords:	Ant Lion Optimizer Grey Wolf Optimizer Dragonfly Optimization Algorithm Firefly Algorithm Flower Pollination Algorithm Whale Optimization Algorithm Cat Swarm Optimization Bat Algorithm Particle Swarm Optimization Gravitational Search Algorithm
Issue Date:	Nov-2018
Publisher:	International Journal of Mechanical Engineering & Technology (IJMET)
Abstract:	The objective functions used in Engineering Optimization are complex in nature with many variables and constraints. Conventional optimization tools sometimes fail to give global optima point. Very popular methods like Genetic Algorithm, Pattern Search, Simulated Annealing, and Gradient Search are useful methods to find global optima related to engineering problems. This paper attempts to review new nontraditional optimization algorithms which are used to solve such complicated engineering problems to obtain global optimum solutions
URI:	http://www.iaeme.com/MasterAdmin/Journal_uploads/IJMET/VOLUME_9_ISSUE_11/IJMET_09_11_025.pdf http://localhost:8080/xmlui/handle/123456789/1145
ISSN:	Print:0976-6340 Online:0976-6359
Appears in Collections:	International Journals

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