نتایج جستجو برای: binary cuckoo optimization
تعداد نتایج: 430719 فیلتر نتایج به سال:
Environmental Economic Load Dispatch with Quadratic Fuel Cost Function Using Cuckoo Search Algorithm
In this paper, a Cuckoo Search Algorithm (CSA) is proposed for solving environmental economic load dispatch (EELD) problem with quadratic fuel function. Cuckoo Search is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species for solving optimization problems with promising results. ...
─ Cuckoo Search (CS) is a new met heuristic algorithm. It is being used for solving optimization problem. It was developed in 2009 by XinShe Yang and Susah Deb. Uniqueness of this algorithm is the obligatory brood parasitism behavior of some cuckoo species along with the Levy Flight behavior of some birds and fruit flies. Cuckoo Hashing to Modified CS have also been discussed in this paper. CS ...
abstract: regarding the growing use of distributed generation resources, optimal design of these units is necessary in the power system especially in the distribution network. in this paper, cuckoo optimization algorithm with multiple purposes was used to determine optimal location and size of distributed generation resources. the investigated purposes include reducing line losses, reducing med...
An effective hybrid cuckoo search algorithm (CS) with improved shuffled frog-leaping algorithm (ISFLA) is put forward for solving 0-1 knapsack problem. First of all, with the framework of SFLA, an improved frog-leap operator is designed with the effect of the global optimal information on the frog leaping and information exchange between frog individuals combined with genetic mutation with a sm...
Hard optimization problems that cannot be solved within reasonable time by standard, mathematical, deterministic methods are of great practical interest. Metaheuristics inspired by nature were recently successfully used for such problems. These metaheuristics are based on random Monte-Carlo search guided by simulation of some nature intelligence, especially evolution and swarm intelligence. One...
Among most machine learning algorithms for optimization problem including meta-heuristic search algorithms, the solution is drawn like a moth to a flame and cannot keep away. The track of chaotic variable can travel ergodically over the whole search space. In general, the chaotic variable has special characters, i.e., ergodicity, pseudo-randomness and irregularity. To enrich the searching behav...
Automatic generation control (AGC) is added in power system to ensure constancy in frequency and tie-line power of an interconnected multi-area power system. In this article, proportional integral (PI) controlled based AGC of two-area hydrothermal system is solved by cuckoo optimization algorithm (COA). It is one of the most powerful stochastic real parameter optimization in current use. The de...
Grid computing incorporates dispersed resources to work out composite technical, industrial, and business troubles. Thus a capable scheduling method is necessary for obtaining the objectives of grid. The disputes of parallel computing are commencing with the computing resources for the number of jobs and intricacy, craving, resource malnourishment, load balancing and efficiency. The risk stumbl...
The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we introduce a new algorithm, MAKHA, which is a hybrid between Monkey Algorithm (MA and Krill Herd Algorithm (KHA). Its performance is compared with the two original algorithms along with Cuckoo S...
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