Simple local search problems that are hard to solve
SIAM Journal on Computing
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
New ideas in optimization
Improvement of genetic algorithm performance for identification of cultivation process models
EC'08 Proceedings of the 9th WSEAS International Conference on Evolutionary Computing
MMAS and ACS for GPS surveying problem
EC'08 Proceedings of the 9th WSEAS International Conference on Evolutionary Computing
Memetic Simulated Annealing for the GPS Surveying Problem
Numerical Analysis and Its Applications
Hybrid ACO algorithm for the GPS surveying problem
LSSC'09 Proceedings of the 7th international conference on Large-Scale Scientific Computing
| Hi-index | 0.00 |
This paper describes metaheuristic algorithm based on simulated annealing method,which is a nature-inspired method, to analyze and improve the efficiency of the design of Global Positioning System (GPS) surveying networks. Within the context of satellite surveying, a positioning network can be defined as a set of points which are coordinated by placing receivers on these point to determine sessions between them. The problem is to search for the best order in which these sessions can be observed to give the best possible schedule. The same problem arise in Mobile Phone surveying networks. Several case studies have been used to experimentally asses the performance of the proposed approach in terms of solution quality and computational effort.