Abstract
Being inspired by natural phenomena and available biological processes in the nature is one of the difficult methods of problem solving in computer sciences. Evolutionary methods are a set of algorithms that are inspired from the nature and are based on their evolutionary mechanisms. Unlike other optimizing methods of problem solving, evolutionary algorithms do not require any prerequisites and usually offer solutions very close to optimized answers. Based on their behavior, evolutionary algorithms are divided into two categories of biological processes based on plant behavior and animal behavior. Various evolutionary algorithms have been proposed so far to solve optimization problems, some of which include evolutionary algorithm of invasive weed and flower pollination algorithm that are inspired by plants and krill algorithm inspired by the animal algorithm of sea animals. In this paper, a comparison is made for the first time between the accuracy and rate of involvement in local optimization of these new evolutionary algorithms to identify the best algorithm in terms of efficiency. Results of various tests show that invasive weed algorithm is more efficient and accurate than flower pollination and krill algorithms.
Highlights
Evolution is a set of processes through which creatures have gradually learnt how to overcome the problems surrounding them and better interact with the environmental changes around them
Evolutionary algorithms are a set of intelligent search algorithms that are able to search in the problem environment and be convergent with efficient answers with enough accuracy (Dasgupta and Michalewicz, 2013)
Evolutionary algorithms perform based on different processes like genetics, evolution, ecosystem, swarm intelligence, etc.Charles Darwin has defined a set of fundamental laws for evolutionary rules that form the base of the science of Evolution
Summary
Evolution is a set of processes through which creatures have gradually learnt how to overcome the problems surrounding them and better interact with the environmental changes around them. Natural selection is considered one of the key terms in evolution and is defined as the process that creates different and various genes in animals over time and is known as one of the factors of formation of new species in nature The environment surrounding these creatures can influence their characteristics and species that have become adapted to the environmental changes over time will continue living. One of evolutionary algorithms that is formed based on plants behaviors and the competition between them is invasive weed algorithm (Mehrabian and Lucas, 2006) In this algorithm, any plant that is more adapted is more likely to survive by producing more seeds. Evolutionary algorithms attempt to use biological, social and natural processes to solve difficult problems and overcome available challenges like these phenomena. The evolutionary algorithms of invasive weed and flower pollination as algorithms inspired by plants and krill algorithm as the evolutionary algorithm of animals (Alavi and Gandomi, 2012) will be investigated and in the following the accuracy and convergence of these evolutionary algorithms will be compared using a set of benchmark functions
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