Software test suite optimization is one of the most important issue in software testing as testing consumes a lot of time in executing redundant test cases. In this paper, we have proposed and implemented a new approach for test suite optimization, namely, Mutated Artificial Bee Colony. Artificial Bee colony algorithm combines local search carried out by employed and onlooker bees with global s...

In recent years several bee inspired optimization techniques have been proposed. These methods are either based on the bees’ foraging or mating behavior. Both foraging and mating regulate distributions outside (foraging) or within a colony (mating). Foraging determines the ratio of individuals that explore the surroundings for new food sources and those that exploit known food sources, while ma...

Many different earning algorithms used for getting high performance in mathematics and statistical tasks. Recently, an Artificial Bee Colony (ABC) developed by Karaboga is a nature inspired algorithm, which has been shown excellent performance with some standard algorithms. The hybridization and improvement strategy made ABC more attractive to researchers. The two famous improved algorithms are...

Routing and Wavelength Assignment (RWA) problem in all-optical networks assumes determining the routes and wavelengths to be used to create the lightpaths for connection requests. The RWA problem belongs to a class of difficult combinatorial optimization problems. We propose the Bee Colony Optimization (BCO) heuristic algorithm tailored for the RWA problem (BCO–RWA) in all-optical networks with...

The aim of this research is the development of a reliable tool to detect early signs of breast cancer in mammographic images. Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death of female worldwide. Mammogram is one of the most excellent technologies currently being used for diagnosing breast cancer. In this paper, the Enhanced Artificial Bee Colony Optim...

Environmental pollution and emissions, along with the increasing production and distribution of goods, have placed the future of humanity at stake. Today, measures such as the extensive reduction in emissions, especially of CO2 and CO, have been emphasized by most researchers as a solution to the problem of environmental protection. This paper sought to explore production routing pro...

In this paper, a cardinality constrained mean-variance model is introduced for the portfolio optimization problems. This model is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. The use of heuristic algorithms in this case is necessary. Some studies have investigated the cardinality constrained mean-variance model using heuristic algorithm. But alm...

A statistical analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation in the Bee Colony Optimization algorithm (BCO) is presented in this paper. The Bee Colony Optimization meta-heuristic belongs to the class of Nature-Inspired Algorithms. The objective of the work is based on the main reasons for the analysis of the approach with Interval Type-2 Fuzzy Logic to find t...

in this paper proposes a fuzzy multi-objective hybrid genetic and bee colony optimization algorithm(ga-bco) to find the optimal restoration of loads of power distribution network under fault.restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. to improve the efficiency of restoration and facilitate theactivity...

K-means algorithm is sensitive to initial cluster centers and its solutions are apt to be trapped in local optimums. In order to solve these problems, we propose an optimized artificial bee colony algorithm for clustering. The proposed method first obtains optimized sources by improving the selection of the initial clustering centers; then, uses a novel dynamic local optimization strategy utili...