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...

Cities are growing and encountering many changes over time due to population growth and migration. Identification and detection of these changes play important roles in urban management and sustainable development. Urban growth models are divided into two main categories: first cellular models which are further divided into experimental, dynamic, and integrated models and second vector models. ...

Wireless Sensor Networks (WSNs) are networks of autonomous nodes used for monitoring an environment. In designing WSNs, one of the main issues is limited energy source for each sensor node. Hence, offering ways to optimize energy consumption in WSNs which eventually increases the network lifetime is strongly felt. Gravitational Search Algorithm (GSA) is a novel stochastic population-based meta-...

Gravitational search algorithm (GSA) has been recently presented as a new heuristic search algorithm with good results in real-valued and binary encoded optimization problems which is categorized in swarm intelligence optimization techniques. The aim of this article is to show that GSA is able to find multiple solutions in multimodal problems. Therefore, in this study, a new technique, namely N...