In this paper, we propose an improved gravitational search algorithm named GSABC. The algorithm improves gravitational search algorithm (GSA) results improved by using artificial bee colony algorithm (ABC) to solve constrained numerical optimization problems. In GSA, solutions are attracted towards each other by applying gravitational forces, which depending on the masses assigned to the soluti...

The idea of exploiting Global Sensitivity Analysis (GSA) to make Evolutionary Algorithms more effective seems very attractive: intuitively, a probabilistic analysis can prove useful to a stochastic optimisation technique. GSA, that gathers information about the behaviour of functions receiving some inputs and delivering one or several outputs, is based on computationally-intensive stochastic sa...

The presence of a Gender and Sexuality Alliance (GSA) reduces risk for sexual gender minority (SGM) youth across variety domains, but little is known about the adult advisor-level variables contributing to these observed benefits. This study explored relationships between advisors' tenure, receipt professional development, self-efficacy, social emotional competencies (SECs). Participants (N = 1...

Gravitational search algorithm (GSA) is a type of optimization algorithm based on the law of gravity and mass interactions, which is lacking of memory ability. To enhance particle memory ability and search accuracy of GSA, a modified GSA (MGSA) is developed. MGSA adopts the idea of local optimum solution and global optimum solution from particle swarm optimization (PSO) algorithm into GSA. Furt...

In this paper we obtain several tight bounds on different types of alliance numbers of a graph, namely (global) defensive alliance number, global offensive alliance number and global dual alliance number. In particular, we investigate the relationship between the alliance numbers of a graph and its algebraic connectivity, its spectral radius, and its Laplacian spectral radius.

The gravitational search algorithm (GSA) is a kind of swarm intelligence optimization algorithm based on the law of gravitation. The parameter initialization of all swarm intelligence optimization algorithms has an important influence on the global optimization ability. Seen from the basic principle of GSA, the convergence rate of GSA is determined by the gravitational constant and the accelera...

Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closel...

A global o ensive alliance in a graph G = (V; E) is a subset S of V such that for every vertex v not in S at least half of the vertices in the closed neighborhood of v are in S. The cardinality of a minimum size global o ensive alliance in G is called the global o ensive alliance number of G. We give an upper bound on the global (strong) o ensive alliance number of a graph in terms of its degre...

In this paper we describe a web search agent, called Global Search Agent (hereafter GSA for short). GSA integrates and enhances several search techniques in order to achieve significant improvements in the user-perceived quality of delivered information as compared to usual web search engines. GSA features intelligent merging of relevant documents from different search engines, anticipated sele...

For a graph G = (V,E), a non-empty set S ⊆ V is a global offensive alliance if for every v ∈ V − S, at least half of the vertices from the closed neighborhood of v are in S. A set S ⊆ V is a global strong offensive alliance if for each vertex v ∈ V −S, a strict majority of the vertices of the closed neighborhood of v are in S. The cardinality of a minimum global (strong) offensive alliance of a...