The Patch-Levy-Based Bees Algorithm Applied to Dynamic Optimization Problems
نویسندگان
چکیده
منابع مشابه
Honey-bees Optimization Algorithm Applied to Path Planning Problem
Autonomous systems assume intelligent behaviour with capabilities of dealing in complex and changing environments. Problem of path planning, which can be observed as an optimization problem, seems to be of high importance for arising of intelligent behaviour for different real-world problem domains. Swarm intelligence has gained increasingly high interest among the researchers from different ar...
متن کاملIntroducing a new meta-heuristic algorithm based on See-See Partridge Chicks Optimization to solve dynamic optimization problems
The SSPCO (See-See Particle Chicks Optimization) is a type of swarm intelligence algorithm derived from the behavior of See-See Partridge. Although efficiency of this algorithm has been proven for solving static optimization problems, it has not yet been tested to solve dynamic optimization problems. Due to the nature of NP-Hard dynamic problems, this algorithm alone is not able to solve such o...
متن کاملConstrained Multi-Objective Optimization Problems in Mechanical Engineering Design Using Bees Algorithm
Many real-world search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using classical optimization methods, this paper presents a Multi-Objective Bees Algorithm (MOBA) for solving the multi-objective optimal of mechanical engineering problems design. In the pre...
متن کاملOptimization methodology based on neural networks and reference point algorithm applied to fuzzy multiobjective optimization problems
Artificial neural networks are massively paralleled distributed computation and fast convergence and can be considered as an efficient method to solve real-time optimization problems. In this paper, we propose reference point based neural network algorithm for solving fuzzy multiobjective optimization problems MOOP. The target is to identify the Pareto-optimal region closest to the reference po...
متن کاملComparative Study of Particle Swarm Optimization and Genetic Algorithm Applied for Noisy Non-Linear Optimization Problems
Optimization of noisy non-linear problems plays a key role in engineering and design problems. These optimization problems can't be solved effectively by using conventional optimization methods. However, metaheuristic algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) seem very efficient to approach in these problems and became very popular. The efficiency of these ...
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: Discrete Dynamics in Nature and Society
سال: 2017
ISSN: 1026-0226,1607-887X
DOI: 10.1155/2017/5678393