A High-Speed, Performance-Optimization Algorithm Based on a Gravitational Approach

Abstract

Recently a novel heuristic search algorithm, called Gravitational Search Algorithm (GSA), which is based on the law of gravity and mass interactions, has been proposed. Although GSA has high performance in solving various optimization problems, it has some time consuming computations for calculation of the total force on each mass which makes the speed of optimization low. In this paper we introduce a new approach, which improves GSA's speed considerably. Our approach is based on the multi-agent systems where multiple agents are the mechanism used to express the parallelism. In multi-agent based GSA, complex problems are decomposed into smaller and simpler components that are handled by different agents in the system. Our experimental results show our multi-agent based GSA approach provides a high performance and high speed optimization methodology that can help scientists in a variety of science and engineering computations.

Tuned‐TSC based SVC for reactive power compensation and harmonic reduction in unbalanced distribution system

“…Thus, they represent good optimal solution to the problem and move more slowly than lighter ones. In GSA, each mass has four identifications: its position, its inertial mass, and its active and passive gravitational mass [42][43][44][45][46]. The position of the mass is equivalent to a solution of the problem and its gravitational and inertial masses are calculated by using a fitness function.…”

“…The switching function of TCR is developed considering reduction of all odd harmonics (up to 31st order) from the TCR voltage waveform. Gravitational search algorithm (GSA) [42][43][44][45][46] has been used to calculate the optimised switching angles off-line although any other standard heuristic search based technique can be used for this purpose. The switching angles are computed off-line at close intervals of modulation indices which can be expressed as the ratio between fundamental component of reactor voltage to the rated load voltage.…”

Gravitational Search Algorithms in Data Mining: A Survey

“…The problem of diversity loss has been removed by an improved version of QGSA [19]. To improve the speed a GSA, a multi-agent based GSA has been proposed by Nanji et al [20].…”

A Review on Gravitational Search Algorithm and its Applications to Data Clustering & Classification

“…The perfo rmance of IQGSA evaluated with seven minimizat ion benchmark functions and compared with original GSA & QGSA in which IQGSA has given better results than others. To improve computational cost of original GSA Naji et al [48] have developed a mu lti agent based GSA wh ich is new version of GSA. In mu lti agent based GSA, operations have performed in parallel rather than sequential.…”