Based on introducing two optimization algorithms, group search optimization (GSO) algorithm and particle swarm optimization (PSO) algorithm, a new hybrid optimization algorithm which named particle swarm-group search optimization (PS-GSO) algorithm is presented and its application to optimal structural design is analyzed. The PS-GSO is used to investigate the spatial truss structures with discr...

This article introduces two swarm intelligent algorithms, a group search optimizer (GSO) and an artificial fish swarm algorithm (AFSA). A single intelligent algorithm always has both merits in its specific formulation and deficiencies due to its inherent limitations. Therefore, we propose a mixture of these algorithms to create a new hybrid optimization algorithm known as the group search-artif...

This paper utilizes the improved group search optimization algorithm for optimal reactive power dispatch (ORPD). The ORPD problem is a non-linear, non-convex optimization problem which has various decision variables such as compensation capacitor proportions, voltage of generators and the tap position of tap changing transformers. In this paper the multi-objective ORPD considering loss, voltage...

Glowworm swarm optimization (GSO) algorithm is a new intelligent optimization algorithm. Based on the problems of GSO, such as easy to fall into local optimum, slow convergence speed and low optimization precision, an improved GSO with group division is presented. Using shuffled frog leaping algorithm (SFLA), glowworms are divide into different ethnic groups, and local search and global informa...

Artificial Neural Networks (ANNs) have been applied to machine condition monitoring. This paper first addresses a ANN trained by Group Search Optimizer (GSO), which is a novel Swarm Intelligent (SI) optimization algorithm inspired by animal social foraging behaviour. The global search performance of GSO has been proven to be competitive to other evolutionary algorithms, such as Genetic Algorith...

This note compares the performance of two multidimensional search and optimization algorithms: Group Search Optimizer and Central Force Optimization. GSO is a new state-of-theart algorithm that has gained some notoriety, consequently providing an excellent yardstick for measuring the performance of other algorithms. CFO is a novel deterministic metaheuristic that has performed well against GSO ...

Group search optimizer(GSO) is a new novel optimization algorithm by simulating animal behaviour. It uses the Gbest topology structure, which leads to rapid exchange of information among particles. So,it is easily trapped into a local optima when dealing with multi-modal optimization problems. In this paper,inspiration from the Newman and Watts model,a improved group search optimizer with inter...

Multimodal optimization aims at finding multiple global and local optima (as opposed to a single solution) of a function, so that the user can have a better knowledge about different optimal solutions in the search space and as and when needed, the current solution may be switched to another suitable one while still maintaining the optimal system performance. Evolutionary Algorithms (EAs) due t...