New directional bat algorithm for continuous optimization problems
نویسندگان
چکیده
منابع مشابه
An Improved Bat Algorithm with Grey Wolf Optimizer for Solving Continuous Optimization Problems
Metaheuristic algorithms are used to solve NP-hard optimization problems. These algorithms have two main components, i.e. exploration and exploitation, and try to strike a balance between exploration and exploitation to achieve the best possible near-optimal solution. The bat algorithm is one of the metaheuristic algorithms with poor exploration and exploitation. In this paper, exploration and ...
متن کاملCultural Ant Algorithm for Continuous Optimization Problems
In order to overcome prematurity of ant colony algorithm, the conception of belief space originated in cultural algorithm is introduced, and a new cultural ant algorithm is proposed for continuous optimization problems. Firstly, the coding scheme for ant colony algorithm to solve continuous optimization problems is discussed. Then belief space is brought in, and designed as the form of two part...
متن کاملFirefly Mating Algorithm for Continuous Optimization Problems
This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females...
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 کاملPSOLVER: A new hybrid particle swarm optimization algorithm for solving continuous optimization problems
This study deals with a new hybrid global–local optimization algorithm named PSOLVER that combines particle swarm optimization (PSO) and a spreadsheet ‘‘Solver” to solve continuous optimization problems. In the hybrid PSOLVER algorithm, PSO and Solver are used as the global and local optimizers, respectively. Thus, PSO and Solver work mutually by feeding each other in terms of initial and sub-i...
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: Expert Systems with Applications
سال: 2017
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2016.10.050