Software testing is an important activity that is carried out during the software development life cycle. Regression testing means re-executing test cases from existing test suites to assure that the modifications done to the existing software have no adverse effects. During regression testing, new test cases are not created but previously created test cases are reexecuted. The ideal regression...

To make glowworm swarm optimization (GSO) algorithm solve multi-extremum global optimization more effectively, taking into consideration the disadvantages and some unique advantages of GSO, the paper proposes a hybrid algorithm of Broyden–Fletcher–Goldfarb– Shanno (BFGS) algorithm and GSO, i.e., BFGS-GSO by adding BFGS local optimization operator in it, which can solve the problems effectively ...

Power generated in generating station is transmitted through transmission lines and fed to the consumers through distribution substation. The power distributed in to the network has losses, which is greater in distribution system than the transmission system. This problem could be addressed by placing capacitor at strategic location due to which the kW loss can be minimized by improving the vol...

Group Search Optimizer(GSO) is one of the best algorithms, and is very new in the field of Evolutionary Computing. It is very robust and efficient algorithm, which is inspired by animal searching behaviour. The paper describes an application of GSO to clustering of networks. We have tested GSO against five standard benchmark datasets and the algorithm is proven to be very competitive in terms o...

In this paper, a novel hybrid glowworm swarm optimization (HGSO) algorithm is proposed. Firstly, the presented algorithm embeds predatory behavior of artificial fish swarm algorithm (AFSA) into glowworm swarm optimization (GSO) algorithm and combines the improved GSO with differential evolution (DE) on the basis of a two-population co-evolution mechanism. Secondly, under the guidance of the fea...

Cryptanalysis with Computational Intelligence has gained much interest in recent years. This paper presents an approach for breaking the key used in Simplified-Data Encryption Standard (S-DES) using Genetic algorithm (GA), Particle Swarm Optimization (PSO) and a novel approach called Genetic Swarm Optimization (GSO) obtained by combining the effectiveness of GA and PSO. Ciphertext-only attack i...

Highly multimodal function optimization is similar to many other optimization problems requiring many iterations and large number of function evaluations. Glowworm Swarm Optimization (GSO) is one of the common swarm intelligence algorithms, where GSO has the ability to optimize multimodal functions efficiently. Locating the peaks of a high-dimensional multimodal function requires a large popula...

This study introduces an effective population-based optimization algorithm, namely the Golden Search Optimization Algorithm (GSO), for numerical function optimization. The new algorithm has a simple but strategy solving complex problems. GSO starts with random possible solutions called objects, which interact each other based on mathematical model to reach global optimum. To provide fine balanc...

We research maximum range expansion using a fixed number of mobile wireless nodes along a line which do distributed MIMO (Multiple Input Multiple Output) in diversity configuration, also known as cooperative transmission (CT). The emphasis is on optimal clusters and locations of these clusters to maximize the multi-hop reach along the line based on the swarm intelligence algorithms which are th...

Methods to deal with Multimodal Optimization Problems (MMOP) can be classified in three main approaches, regarding the number and the type of desired solutions. In general, methods can be applied to find: (1) only one global solution; (2) all global solutions; and (3) all local solutions of a given MMOP. The simultaneous capture of several solutions of MMOPs without parameter adjustment is stil...