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...

Although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. This paper deals with scheduling jobs in lot streaming flexible flow line problems. The paper mathematically formulates the problem by a mixed integer linear programming model. This model solves small instances to optimality. Moreo...

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...

Feature selection plays an important role in data mining and pattern recognition, especially in the case of large scale data. Feature selection is done due to large amount of noise and irrelevant features in the original data set. Hence, the efficiency of learning algorithms will increase incredibly if these irrelevant data are removed by this procedure. A novel approach for feature selection i...

In data mining, clustering is one of the important issues for separation and classification with groups like unsupervised data. In this paper, an attempt has been made to improve and optimize the application of clustering heuristic methods such as Genetic, PSO algorithm, Artificial bee colony algorithm, Harmony Search algorithm and Differential Evolution on the unlabeled data of an Iranian bank...

The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a sing...

This paper proposes a new artificial bee colony algorithm with quantum theory and the chaotic local search strategy (QCABC), and uses it to solve the optimal power flow (OPF) problem. Under the quantum computing theory, the QCABC algorithm encodes each individual with quantum bits to form a corresponding quantum bit string. By determining each quantum bits value, we can get the value of the ind...

Determination of optimum location for drilling a new well not only requires engineering judgments but also consumes excessive computational time. Additionally, availability of many physical constraints such as the well length, trajectory, and completion type and the numerous affecting parameters including, well type, well numbers, well-control variables prompt that the optimization approaches b...

The artificial bee colony (ABC) algorithm has been a well-known swarm intelligence algorithm, which assimilates the cooperating behavior of bees when seeking for nectar sources. Aiming to improve the conventional ABC algorithm, we focus on the re-initialization phase. In this paper, an overall-degradation-oriented artificial bee colony (OD-ABC) algorithm is proposed, pursuing to fight against p...