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What is Gravitational Search Algorithm

Chapter 12
Handbook of Research on Swarm Intelligence in Engineering
Gravitational Search Algorithm (GSA) is a heuristic optimization algorithm which has been gaining much interest among the scientific community recently. GSA is a nature inspired algorithm based on the Newton’s famous law of gravity and the law of motion. GSA is classified under population-based method and is reported to be more instinctive. In GSA, the agent has four parameters which are position, inertial mass, active gravitational mass, and passive gravitational mass. GSA is a memory-less algorithm. However, it works efficiently like the algorithms with memory.
Published in Chapter:
Swarm Intelligence-Based Optimization for PHEV Charging Stations
Imran Rahman (Universiti Teknologi Petronas, Malaysia), Pandian Vasant (University of Technology Petronas, Malaysia), Balbir Singh Mahinder Singh (Universiti Teknologi Petronas, Malaysia), and M. Abdullah-Al-Wadud (King Saud University, Saudi Arabia)
Copyright: © 2015 |Pages: 32
DOI: 10.4018/978-1-4666-8291-7.ch012
Abstract
In this chapter, Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO) technique were applied for intelligent allocation of energy to the Plug-in Hybrid Electric Vehicles (PHEVs). Considering constraints such as energy price, remaining battery capacity, and remaining charging time, they optimized the State-of-Charge (SoC), a key performance indicator in hybrid electric vehicle for the betterment of charging infrastructure. Simulation results obtained for maximizing the highly non-linear objective function evaluates the performance of both techniques in terms of global best fitness and computation time.
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More Results
Chapter 12
Hybridization of Biogeography-Based Optimization and Gravitational Search Algorithm for Efficient Face Recognition
Gravitational search algorithm is an optimization algorithm based on the law of gravity and mass interactions.
Published in Chapter: Hybridization of Biogeography-Based Optimization and Gravitational Search Algorithm for Efficient Face Recognition; From: Advanced Metaheuristic Methods in Big Data Retrieval and Analytics
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Chapter 27
Gravitational Search Algorithm: Concepts, Variants, and Operators
A swarm intelligence algorithm based on the Newtonian gravity and the laws of motion.
Published in Chapter: Gravitational Search Algorithm: Concepts, Variants, and Operators; From: Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics
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Chapter 18
Hybrid Particle Swarm and Gravitational Search Optimization Techniques for Charging Plug-In Hybrid Electric Vehicles
Gravitational Search Algorithm (GSA) is a heuristic optimization algorithm which has been gaining much interest among the scientific community recently. GSA is a nature inspired algorithm based on the Newton’s famous law of gravity and the law of motion. GSA is classified under population-based method and is reported to be more instinctive. In GSA, the agent has four parameters which are position, inertial mass, active gravitational mass, and passive gravitational mass. GSA is a memory-less algorithm. However, it works efficiently like the algorithms with memory.
Published in Chapter: Hybrid Particle Swarm and Gravitational Search Optimization Techniques for Charging Plug-In Hybrid Electric Vehicles; From: Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics
Full Text Chapter Download: US $37.50 Add to Cart
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