An Improved Central Force Optimization Algorithm for Multimodal Optimization
نویسندگان
چکیده
منابع مشابه
Improved Cuckoo Search Algorithm for Global Optimization
The cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. To enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. Normally, the parametersof the cuckoo search are kept constant. This may lead todecreasing the efficiency of the algorithm. To cop...
متن کاملimproved cuckoo search algorithm for global optimization
the cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. to enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. normally, the parametersof the cuckoo search are kept constant. this may lead todecreasing the efficiency of the algorithm. to cop...
متن کاملAn Improved Firefly Algorithm for Optimization Problems
Optimization problem is one of the most difficult and challenging problems that has received considerable attention over the last decade. Researchers have been constantly investigating better ways to solve it. Recently, one optimization technique called firefly algorithm has gained the interest of many researchers. This algorithm is a type of swarm intelligence algorithm based on the reaction o...
متن کاملAn improved genetic algorithm for multidimensional optimization of precedence-constrained production planning and scheduling
Integration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensional optimization at the same time: what to make, how many to make, where to make and the order to make. It is a combinatorial,...
متن کاملAn 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 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: Journal of Applied Mathematics
سال: 2014
ISSN: 1110-757X,1687-0042
DOI: 10.1155/2014/895629