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...

In this paper, a hybrid method for solving multi-objective problem has been provided. The proposed method is combining the ε-Constraint and the Cuckoo algorithm. First the multi objective problem transfers into a single-objective problem using ε-Constraint, then the Cuckoo optimization algorithm will optimize the problem in each task. At last the optimized Pareto frontier will be drawn. The adv...

The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or maximum. One of the ways inaccurate optimization is meta-heuristics so that Inspired by nature, ...

The Partial Transmit Sequence which reduces the PAPR (Peak-to-Average Power Ratio) in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system using a novel optimization algorithm is proposed in this study. This novel optimization algorithm is based on a hybrid of Bacterial Foraging Optimization (BFO) and Modified Cuckoo Search algorithm (MCS) and is thus cal...

in the science of operation research and decision theory, selection is the most important process. selection is a process that studies multiple qualitative and quantitative criteria, related to the science of management, which are mostly incompatible with each other. the multi criteria selection of a renewable energy portfolio is one of the main issues considered in multi criteria literature. i...

Today, in computer science, a computational challenge exists in finding a globally optimized solution from an enormously large search space. Various meta-heuristic methods can be used for finding the solution in a large search space. These methods can be explained as iterative search processes that efficiently perform the exploration and exploitation in the solution space. In this context, thre...

Nature-inspired algorithms (NIAs) have gained a significant popularity in recent years to tackle hard real world problems and solve complex optimization functions whose actual solution does not exist. Many new algorithms have been developed which show their capabilities almost in every aspect, where rapid solutions are needed. A survey of the NIAs that are used to find the optimal digital image...

The Cuckoo search algorithm is a recent addition to metaheuristic techniques. It simulates the breeding behaviour of certain cuckoo species into a numerical optimization technique. Cuckoo birds lay their eggs in the nests of other host birds so that their chicks when hatched can be nurtured by the host birds. The optimum design algorithm presented for moment resisting steel frames is based on t...

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...

In this paper, optimal thresholds for multi-level thresholding in an image are obtained by maximizing the Tsallis entropy using cuckoo search algorithm. The method is considered as a constrained optimization problem. The solution is obtained through the convergence of a meta-heuristic search algorithm. The proposed algorithm is tested on standard set of images. The results are then compared wit...