Gravitational search algorithm (GSA) is a swarm intelligence optimization algorithm that shares many similarities with evolutionary computation techniques. However, the GSA is driven by the simulation of a collection of masses which interact with each other based on the Newtonian gravity and laws of motion. Inspired by the classical GSA and quantum mechanics theories, this work presents a novel...

The speed profile of the train will be determined according to criteria such as safety, travel convenience, and the type of electric motor used for traction. Due to the passengers and cargo on the train, the electric train load is constantly changing. This will require reassigning the speed controller’s parameters of the electric train. For this purpose, the Gravitational Search optimization Al...

Abstract: One of the equipment that can help improve distribution system status today and reduce the cost of fault time is remote control switches (RCS). Finding the optimal location and number of these switches in the distribution system can be modeled with various objective functions as a nonlinear optimization problem to improve system reliability and cost. In this article, a particle swarm ...

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...

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...

Damping of inter-area electromechanical oscillations is one of the major challenges to the electric power system operators. This paper presents Gravitational Search Algorithm (GSA) for tuning Static Synchronous Series Compensator (SSSC) based damping controller to improve power system oscillation stability. In the proposed algorithm, the searcher agents are a collection of masses which interact...

Gravitational search algorithm (GSA) is a new member of swarm intelligence algorithms. It stems from Newtonian law of gravity and motion. The performance of synchronous GSA (S-GSA) and asynchronous GSA (A-GSA) is studied here using statistical analysis. The agents in S-GSA are updated synchronously, where the whole population is updated after each member’s performance is evaluated. On the other...

Gravitational Search Algorithm (GSA) is a newly heuristic algorithm inspired by nature which utilizes Newtonian gravity law and mass interactions. It has captured much attention since it has provided higher performance in solving various optimization problems. This study hybridizes the GSA and chaotic equations. Ten chaotic-based GSA (GSA-CM) methods, which define the random selections by diffe...

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...

This paper proposes an extension of the Gravitational Search Algorithm (GSA) to multiobjective optimization problems. The new algorithm, called Non-dominated Sorting GSA (NSGSA), utilizes the non-dominated sorting concept to update the gravitational acceleration of the particles. An external archive is also used to store the Pareto optimal solutions and to provide some elitism. It also guides t...