Using gravitational force in terrain optimization problems

Optimization problems represent algorithms designed for difficult problems which may require huge amount of space or computational time. Such kind of algorithms bring out solutions which are optimal and at the same time closer to the real life environments where not everything is precise and the possibility of errors is present at every instant. Finding the minimal point in a terrain is a challenge of its own, especially when we are dealing with an unknown area. In order to tackle this problem, we thought of making use of gravitational force, since it is proportionally related to earth center proximity. In an unknown terrain, we spread our agents that are capable to communicate information to one another at randomly generated positions. Later on, each of these agents calculates the gravity variation with altitude at its respective position. Since, we were looking to find the optimal minimum point in the terrain, after the gravity variation with altitude is computed by each agent, the

Optimization problems represent algorithms designed for difficult problems which may require huge amount of space or computational time. Such kind of algorithms bring out solutions which are optimal and at the same time closer to the real life environments where not everything is precise and the possibility of errors is present at every instant. Finding the minimal point in a terrain is a challenge of its own, especially when we are dealing with an unknown area. In order to tackle this problem, we thought of making use of gravitational force, since it is proportionally related to earth center proximity. In an unknown terrain, we spread our agents that are capable to communicate information to one another at randomly generated positions. Later on, each of these agents calculates the gravity variation with altitude at its respective position. Since, we were looking to find the optimal minimum point in the terrain, after the gravity variation with altitude is computed by each agent, the highest gravity is found. This is communicated to the other agents as well and they start moving toward the agent that is currently found at an area with high gravity variation. The agents move toward the high gravity agent with a certain heuristic coefficient. During their path they may encounter other terrain points where the gravitational force is stronger, which would cause a change in the path of other agents making them move toward the newly found position. This is done until an optimal minimum is found by the agents. Our test results so far have been very promising. We aim to develop the algorithm furthermore in order to increase its efficiency and efficacy. We strongly believe that such an algorithm can be used to reach in the unexplored areas of ocean floor, or searching for minerals by minimizing the area of search in an optimal time