In recent years, various heuristic optimization methods have been developed. Many of these methods are inspired by swarm behaviors in nature, such as particle swarm optimization (PSO), firefly algorithm (FA) and cuckoo optimization algorithm (COA). Recently introduced COA, has proven its excellent capabilities, such as faster convergence and better global minimum achievement. In this paper a ne...

Aiming to effectively recognize train center plate bolt loss faults, this paper presents an improved fault detection method. A multi-scale local binary pattern operator containing the local texture information of different radii is designed to extract more efficient discrimination information. An improved teaching-learning-based optimization algorithm is established to optimize the classificati...

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 evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algo...

Computational grid is a hardware and software infrastructure that provides dependable, inclusive and credible to other computing capabilities. Grid computing intercommunicated with a set of computational resources on a large scale. Scheduling independent jobs is an important issues in such areas as computational grid. Scheduling is the process of assigning jobs to resources in order to achieve ...

The assembly sequence optimization problem is challenging as number of sequences rises staggeringly with part count making it combinatorially explosive, tedious and time consuming to solve. A Computer-Aided Process Planning (CAPP) system for robotic assembly by a discrete cuckoo search algorithm has been proposed by us to generate feasible and optimal sequences considering minimization of orien...

As with other nature-inspired algorithms, the cuckoo optimization algorithm (COA) produces a population of candidate solutions to find the (near-) optimal solutions to a problem. In this paper, several modifications, including a dynamic mutation operator, are proposed for this algorithm. Design of experiments is employed to determine factors controlling the value of parameters and the target le...

Portfolio selection is one of the most important and vital decisions that a real or legal person, who invests in stock market should make. The main purpose of this paper is the determination of the optimal portfolio with regard to stock returns of companies, which are active in Tehran’s stock market. For achieving this purpose, annual statistics of companies’ stocks since Farvardin 1387 until E...

The traditional Back Propagation (BP) has some significant disadvantages, such as training too slowly, easiness to fall into local minima, and sensitivity of the initial weights and bias. In order to overcome these shortcomings, an improved BP network that is optimized by Cuckoo Search (CS), called CSBP, is proposed in this paper. In CSBP, CS is used to simultaneously optimize the initial weigh...

Data analysis in cardiovascular diseases is difficult due to large massive of information. All of features are not impressive in the final results. So it is very important to identify more effective features. In this study, the method of feature selection with binary cuckoo optimization algorithm is implemented to reduce property. According to the results, the most appropriate classification fo...