Self-adaptive salp swarm algorithm for engineering optimization problems
نویسندگان
چکیده
منابع مشابه
Self-Adaptive Spider Monkey Optimization Algorithm for Engineering Optimization Problems
Algorithms inspired by intelligent behavior of simple agents are very popular now a day among researchers. A comparatively young algorithm motivated by extraordinary behavior of Spider Monkeys is Spider Monkey Optimization (SMO) algorithm. SMO algorithm is very successful algorithm to get to the bottom of optimization problems. This work presents a self-adaptive Spider Monkey optimization (SaSM...
متن کاملFOA: ‘Following’ Optimization Algorithm for solving Power engineering optimization problems
These days randomized-based population optimization algorithms are in wide use in different branches of science such as bioinformatics, chemical physics andpower engineering. An important group of these algorithms is inspired by physical processes or entities’ behavior. A new approach of applying optimization-based social relationships among the members of a community is investigated in this pa...
متن کاملA Particle Swarm Optimization Algorithm for Mixed-Variable Nonlinear Problems
Many engineering design problems involve a combination of both continuous anddiscrete variables. However, the number of studies scarcely exceeds a few on mixed-variableproblems. In this research Particle Swarm Optimization (PSO) algorithm is employed to solve mixedvariablenonlinear problems. PSO is an efficient method of dealing with nonlinear and non-convexoptimization problems. In this paper,...
متن کاملA Self-adaptive Global Particle Swarm Optimization Algorithm for Unconstrained Optimization Problems
This paper aims to present a self-adaptive global particle swarm optimization (SGPSO) algorithm for solving unconstrained optimization problems. In the new algorithm, the inertia weights are generated based on Gaussian distribution, which is helpful to improve the diversity of the population. In addition, the worst particle is updated by averaging the other particles, which is beneficial to imp...
متن کاملAn Adaptive Quantum Evolutionary Algorithm for Engineering Optimization Problems
Real world problems in engineering domain are typically constraint optimization problems. An Adaptive Quantum Evolutionary Algorithm for solving such problems is proposed in this paper. The proposed technique uses a novel qubits representation for search and optimization and uses feasibility rules for handling constraints. Moreover, it does not need stochastic ranking or niching or other method...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Mathematical Modelling
سال: 2021
ISSN: 0307-904X
DOI: 10.1016/j.apm.2020.08.014