Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. These networks can be trained with gradient descent back propagation. The algorithm is not definite in finding the global minimum of the error function since gradient descent may get stuck ...

Cuckoo search (CS) is a novel biologically inspired algorithm and has been widely applied to many fields. Although some binary-coded CS variants are developed to solve 0-1 knapsack problems, the search accuracy and the convergence speed are still needed to further improve. According to the analysis of the shortcomings of the standard CS and the advantage of the global harmony search (GHS), a no...

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...

Disease forecasting using soft computing techniques is major area of research in data mining in recent years. To classify heart and diabetes diseases, this paper proposes a diagnosis system using cuckoo search optimized rough sets based attribute reduction and fuzzy logic system. The disease prediction is done as per the following steps 1) feature reduction using cuckoo search with rough set th...

In this article using Cuckoo Optimization Algorithm and simple additive weighting method the hybrid COAW algorithm is presented to solve multi-objective problems. Cuckoo algorithm is an efficient and structured method for solving nonlinear continuous problems. The created Pareto frontiers of the COAW proposed algorithm are exact and have good dispersion. This method has a high speed in finding ...

The Graph Coloring Problem (GCP) is one of the most interesting, studied, and difficult combinatorial optimization problems. That is why several approaches were developed for solving this problem, including exact approaches, heuristic approaches, metaheuristics, and hybrid approaches. This paper tries to solve the graph coloring problem using a discrete binary version of cuckoo search algorithm...

Nowadays, due to inherent complexity of real optimization problems, it has always been a challenging issue to develop a solution algorithm to these problems. Single row facility layout problem (SRFLP) is a NP-hard problem of arranging a number of rectangular facilities with varying length on one side of a straight line with aim of minimizing the weighted sum of the distance between all facility...

In this Paper, a novel approach based on Cuckoo search optimization, with dominant eigen value shift for designing robust decentralized load frequency control system for interconnected power system is presented. A proportional integral – derivative (PID) controller is considered to exemplify the optimum parameter search. To demonstrate the robustness of the obtained controller, a two-area non r...

Energy efficient communication is a plenary issue in Wireless Sensor Networks (WSNs). Contemporary energy efficient optimization schemes are focused on reducing power consumption in various aspects of hardware design, data processing, network protocols and operating system. In this paper, optimization of network is formulated by Cuckoo Based Particle Approach (CBPA). Nodes are deployed randomly...

Cuckoo Optimization Algorithm (COA) and Cuckoo Search Algorithm (CS) are two population-based metaheuristics. They are based on the cuckoo’s behavior in their lifestyle and their characteristics in egg laying and breeding. Both algorithms are proposed for continuous optimization problems. In this paper, we propose a comparative study of COA and CS. For this we have proposed a binary version of ...