System reliability-redundancy optimization plays a vital role in realworld applications. Recently, a new meta-heuristic based on swarm intelligence called cat swarm optimization (CSO) algorithm has emerged. CSO is a stochastic optimization paradigm inspired from the natural behavior of cats. To enhance the performance of the CSO algorithm, an improved adaptive CSO (ICSO) algorithm is presented....

This paper introduces a novel multi-objective evolutionary algorithm based on cat swarm optimizationalgorithm (EMCSO) and its application to solve a multi-objective knapsack problem. The multi-objective optimizers try to find the closest solutions to true Pareto front (POF) where it will be achieved by finding the less-crowded non-dominated solutions. The proposed method applies cat swarm optim...

Assembly sequence planning (ASP) is a combinatorial optimization problem in which the order for each part and subassembly is determined. This order is then incorporated into an incrementally expanding subassembly and eventually results in a final assembly. To address this problem, we propose an improved cat swarm optimization (CSO) algorithm and redefine some basic CSO concepts and operations a...

Distributed Systems (DS) are usually complex systems composed of various components and cloud is a common type of DSs. Reliability is a major challenge for the design of cloud systems and DSs in general. In this paper an analytical model to analyze reliability in DSs with regards to task allocation was presented. Subsequently, this model was modified and a new model to analyze reliability in cl...

A stratified random sampling method is preferred for selecting varied populations with outliers. As opposed to plain sampling, increases statistical precision by reducing estimator variance. Before the estimator's variance, stratum boundary identification and data apportionment must be solved. In this study, a Neyman allocation strategy used address determination issue in mixed populations. add...

This paper presents a powerful swarm intelligence metaheuristic optimization algorithm called Dynamic Cat Swarm Optimization. The formulation is through modifying the existing Optimization Algorithm. original suffers from shortcoming of “premature convergence,” which possibility entrapment in local optima usually happens due to off balance between exploration and exploitation phases. Therefore,...

The sand cat swarm optimization algorithm (SCSO) is a recently proposed metaheuristic algorithm. It stimulates the hunting behavior of cat, which attacks or searches for prey according to sound frequency; each aims catch better prey. Therefore, will search location In SCSO algorithm, gradually approach its prey, makes strong exploitation ability. However, in later stage prone fall into local op...