Many heuristic optimization methods have been developed in recent years that are derived from Nature. These methods take inspiration from physics, biology, social sciences, and use of repeated trials, randomization, and specific operators to solve NP-hard combinatorial optimization problems. In this paper we try to describe the main characteristics of heuristics derived from "Newton's law of gravitation", namely a gravitational emulation local search algorithm and a gravitational search algorithm. We also present the detailed survey of distinguishing properties, parameters and applications of these two algorithms.
Keywords
Meta-Heuristic Algorithms, Gravitation, Newton's Law of Gravity, Combinatorial Optimization Problems, NP-Hard
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