The Gravitational Search Algorithm (GSA) is one of the highly regarded population-based algorithms. It has been reported that GSA a powerful global exploration capability but suffers from limitations getting stuck in local optima and slow convergence speed. In order to resolve aforementioned issues, modified version proposed based on levy flight distribution chaotic maps (LCGSA). LCGSA, diversi...

Holding a lasting balance between the water resources and demands has become challenging task for managers, especially in recent years with looming global warming crisis its resulting climatic change effects. This paper focuses on modeling optimized operation of Zayandehrud Reservoir, located west-central Iran, under two fifth-generation climate scenarios called RCP4.5 RCP8.5. A novel variant g...

The efficient use of electrical energy is a topic that has attracted attention for its environmental consequences. On the other hand, induction motors represent the main component in most industries. They consume the highest energy percentages in industrial facilities. This energy consumption depends on the operation conditions of the induction motor imposed by its internal parameters. Since th...

This paper proposes a methodology for an optimal operation of smart distribution network considering the reconfiguration, distributed generation (DG) units allocation and optimally placing shunt capacitors reactive power compensation. In this work, total losses minimization objective is considered. By optimizing objective, it can also results in reduction voltage deviation. The proposed problem...

This paper applies a method, Genetic algorithm with Search area Adaptation (GSA), to the function optimization. In previous study, GSA has proposed for the floorplan design problem and it has shown better performance than several existing methods. We believe that investigation of the searching behavior of the algorithm is important. However, since the floorplan design problem is combinatorial o...

Gravitational search algorithm (GSA) is one of the metaheuristic algorithms that has been popularly implemented in solving various optimization problems. The could perform better highly nonlinear and complex However, GSA also reported to have a weak local ability slow searching speed achieve its convergence. This research proposes two new parameters order improve GSA’s convergence strategy by i...

Supply chain management is a very dynamic operation research problem where one has to quickly adapt according to the changes perceived in environment in order to maximize the benefit or minimize the loss. Therefore we require a system which changes as per the changing requirements. Multi agent system technology in recent times has emerged as a possible way of efficient solution implementation f...

clustering is an effective approach for managing nodes in wireless sensor network (wsn). a new method of clustering mechanism with using binary gravitational search algorithm (bgsa) in wsn, is proposed in this paper to improve the energy consumption of the sensor nodes.reducing the energy consumption of sensors in wsnsis the objective of this paper that is through selecting thesub optimum senso...

Heuristic optimization has shown its superiority in handling identification problem of complicated system, for methods based on heuristic optimization do not have special requirements on model structures of the target system. In this paper, a piecewise function based gravitational search algorithm (PFGSA) is proposed and applied in parameter identification of automatic voltage regulator (AVR) s...

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...