An extensive review of computational intelligence-based optimization algorithms: trends and applications
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METHODOLOGIES AND APPLICATION
An extensive review of computational intelligence-based optimization algorithms: trends and applications Lavika Goel1
Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Area of computational intelligence is gaining researcher’s attention in ongoing trend of technology and evolution due to their high capability to deliver near-optimal solutions. A new hierarchy of algorithms has been proposed in the paper, and they have been organized on the basis of their inspiration sources. The broad two domains of the algorithms are modeling of human mind and nature-inspired intelligence. Nature-inspired computational algorithms being heuristic algorithms are robust and have optimization capability to solve obscure and substantiated problems. The heuristic techniques aim on finding the best possible solution to the query in a satisfiable amount of time. The computational intelligence methods inspired from nature have further been categorized into artificial immune systems, evolutionary algorithms, swarm intelligence, artificial neural networks and geoscience-based algorithms. Geoscience-based domain is the least explored domain in which the algorithms can be developed based on geographic phenomenon taking place on the earth’s surface. An extensive tabular comparison is done among algorithms of all the domains on the basis of various attributes. Also, variants of the algorithms and their implementation in a specific application have been examined. The efficiency and performance of selected algorithms have been compared on clustering and traveling salesman problem for better understanding. Keywords Optimization Computational intelligence Nature-inspired algorithms Swarm intelligence Real-life applications Traveling salesman problem
1 Introduction Optimization refers to maximizing or minimizing a particular function by exploring the solutions in a guided manner, and it is a sought after research area because it includes development of a solution under the given constraints, much like real-world scenarios. Computational intelligence techniques are belonging to a group of algorithms used for optimization. Commonly known as soft computing, their key application is in the area of NP-hard problems to find best possible solutions in polynomial time. Two broad categories are nature-inspired and modeling of human. Modeling of human mind aspect deals with the
Communicated by V. Loia. & Lavika Goel [email protected] 1
Department of Computer Science and Engineering, Malaviya National Institute of Technology (NIT), Jaipur, Rajasthan 302017, India
techniques based on human cognition while nature-inspired domain has been further broken down into artificial immune systems, evolutionary algorithms, swarm intelligence, artificial neural networks and geoscience-based algorithms. The latter are a new domain of algorithms that we have introduced and compared with respect to their affecting factors and equilibrium condition. Before the intr
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