paper-with-me

홈 › Papers

Nature-Inspired Optimization Algorithms: Research Direction and Survey

2021-02-08 · Sachan Rohit Kumar, Kushwaha Dharmender Singh

Nature-inspired algorithms are commonly used for solving the various optimization problems. In past few decades, various researchers have proposed a large number of nature-inspired algorithms. Some of these algorithms have proved to be very efficient as compared to other classical optimization methods. A young researcher attempting to undertake or solve a problem using nature-inspired algorithms is bogged down by a plethora of proposals that exist today. Not every algorithm is suited for all kinds of problem. Some score over others. In this paper, an attempt has been made to summarize various leading research proposals that shall pave way for any new entrant to easily understand the journey so far. Here, we classify the nature-inspired algorithms as natural evolution based, swarm intelligence based, biological based, science based and others. In this survey, widely acknowledged nature-inspired algorithms namely- ACO, ABC, EAM, FA, FPA, GA, GSA, JAYA, PSO, SFLA, TLBO and WCA, have been studied. The purpose of this review is to present an exhaustive analysis of various nature-inspired algorithms based on its source of inspiration, basic operators, control parameters, features, variants and area of application where these algorithms have been successfully applied. It shall also assist in identifying and short listing the methodologies that are best suited for the problem.

📄 PDF Abstract BibTeX arXiv:2102.04013

Code (0)

등록된 구현이 없습니다.

Tasks

Survey

Methods 이 논문이 사용한 방법론

GA Genetic Algorithms are search algorithms that mimic Darwinian biological evolution in order to select and propagate better solutions.
FA 설명 없음
ABC Class of methods in Bayesian Statistics where the posterior distribution is approximated over a rejection scheme on simulations because the likelihood function is…

Similar Papers 제목 키워드 기반

Nature-Inspired Optimization Algorithms: Challenges and Open Problems

2020-03-08 · Xin-She Yang

Many problems in science and engineering can be formulated as optimization problems, subject to complex nonlinear constraints. The solutions of highly nonlinear problems usually require sophisticated optimization algorit…

Benchmarking

Nature Inspired Metaheuristic Effectiveness Used in Phishing Intrusion Detection Systems with Grey Wolf Algorithm Techniques

2022-09-09 · IEEE 2022 9 · Sandra Kopecky ; Catherine Dwyer

This paper discusses research-based findings of applying metaheuristic optimization techniques and nature-inspired algorithms to detect and mitigate phishing attacks. The focus will be on the Grey Wolf nature-inspired me…

Intrusion DetectionMetaheuristic Optimization

A Brief Review of Nature-Inspired Algorithms for Optimization

2013-07-16 · Iztok Fister Jr., Xin-She Yang, Iztok Fister, Janez Brest 외

Swarm intelligence and bio-inspired algorithms form a hot topic in the developments of new algorithms inspired by nature. These nature-inspired metaheuristic algorithms can be based on swarm intelligence, biological syst…

Nature-Inspired Algorithms for Wireless Sensor Networks: A Comprehensive Survey

2020-12-24 · Abhilash Singh, Sandeep Sharma, Jitenda Singh

In order to solve the critical issues in Wireless Sensor Networks (WSNs), with concern for limited sensor lifetime, nature-inspired algorithms are emerging as a suitable method. Getting optimal network coverage is one of…

Survey

Nature Inspired Evolutionary Swarm Optimizers for Biomedical Image and Signal Processing -- A Systematic Review

2023-10-02 · Subhrangshu Adhikary

The challenge of finding a global optimum in a solution search space with limited resources and higher accuracy has given rise to several optimization algorithms. Generally, the gradient-based optimizers converge to the …

ArticlesDenoising