Journal ArticleDOI
A survey of non-gradient optimization methods in structural engineering
Reads0
Chats0
TLDR
A review on non-gradient optimization methods with applications to structural engineering and some remarks on the value of using methods customized for a desired application are made.About:
This article is published in Advances in Engineering Software.The article was published on 2013-05-01. It has received 145 citations till now. The article focuses on the topics: Engineering optimization & Metaheuristic.read more
Citations
More filters
Journal ArticleDOI
Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications
TL;DR: The comparison results on the benchmark functions suggest that MRFO is far superior to its competitors, and the real-world engineering applications show the merits of this algorithm in tackling challenging problems in terms of computational cost and solution precision.
Journal ArticleDOI
Atom search optimization and its application to solve a hydrogeologic parameter estimation problem
TL;DR: A novel physics-inspired metaheuristic optimization algorithm, atom search optimization (ASO), inspired by basic molecular dynamics, is developed to address a diverse set of optimization problems.
Journal ArticleDOI
Water Evaporation Optimization
Ali Kaveh,T. Bakhshpoori +1 more
TL;DR: A novel physically inspired non-gradient algorithm developed for solution of global optimization problems that mimics the evaporation of a tiny amount of water molecules on the solid surface with different wettability which can be studied by molecular dynamics simulations.
Journal ArticleDOI
Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm
TL;DR: The overall comparisons suggest that the optimization performance of AEO outperforms that of other state-of-the-art counterparts, especially for real-world engineering problems, and is more competitive than other reported methods in terms of both convergence rate and computational efforts.
Journal ArticleDOI
Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures
TL;DR: The most important optimization algorithms based on nonlinear physics, how they have been constructed from specific modeling of a real phenomena, and also their novelty in terms of comparison with alternative existing algorithms for optimization are reviewed.
References
More filters
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI
A simplex method for function minimization
John A. Nelder,R. Mead +1 more
TL;DR: A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n 41) vertices of a general simplex, followed by the replacement of the vertex with the highest value by another point.
Journal ArticleDOI
Ant system: optimization by a colony of cooperating agents
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.