An extensive review of computational intelligence-based optimization algorithms: trends and applications

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 inspirati...

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Veröffentlicht in:Soft computing (Berlin, Germany) Jg. 24; H. 21; S. 16519 - 16549
1. Verfasser: Goel, Lavika
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2020
Springer Nature B.V
Schlagworte:
Artificial Intelligence
Artificial neural networks
Clustering
Computational Intelligence
Control
Decision making
Earth science
Earth surface
Engineering
Evolutionary algorithms
Fuzzy sets
Genetic algorithms
Heuristic
Heuristic methods
Immune system
Intelligence
Mathematical Logic and Foundations
Mechatronics
Methodologies and Application
Neural networks
Optimization
Optimization algorithms
Optimization techniques
Robotics
Set theory
Swarm intelligence
Taxonomy
Traveling salesman problem
Traveling salesman problem
Swarm intelligence
Nature-inspired algorithms
Real-life applications
Optimization
Computational intelligence
ISSN:1432-7643, 1433-7479
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Zusammenfassung: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.
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ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-020-04958-w