Title: MMAS and ACS for GPS Surveying Problem
Keywords: Ant Colony Optimization, metaheuristics, GPS surveying

Abstract: Ant Colony Optimization(ACO) have been used successfully to solve hard combinatorial optimization problems. This metaheuristics method is inspired by the foraging behavior of ant colonies, which manage to establish the shortest routes between their colonies to feeding sources and back. In this paper ACO algorithms are developed to provide near-optimal solutions for Global Positioning System surveying problem. In designing Global Positioning System (GPS) surveying network, a given set of earth points must be observed consecutively(schedule). The cost of the schedule is the sum of the time needed to go from one point to another. The problem is to search for the best order in which this observation is executed. Minimizing the cost of this schedule is the goal of this work.



    9th WSEAS International Conference on EVOLUTIONARY COMPUTING(EC’08), pp. 87-91, 2008, Bulgaria,

    Вид: публикация в национален форум