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Computational algorithms inspired by biological processes and evolution

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Title Computational algorithms inspired by biological processes and evolution
 
Creator REDDY, MJ
KUMAR, DN
 
Subject Algorithms
biological processes
evolutionary computation
nonlinear optimization
swarm intelligence
MULTIOBJECTIVE DIFFERENTIAL EVOLUTION
RESERVOIR OPERATION
OPTIMIZATION
SYSTEMS
 
Description In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.
 
Publisher INDIAN ACAD SCIENCES
 
Date 2014-10-15T11:05:20Z
2014-10-15T11:05:20Z
2012
 
Type Article
 
Identifier CURRENT SCIENCE, 103(4)370-380
http://dspace.library.iitb.ac.in/jspui/handle/100/14818
 
Language en