Annals of Operations Research - Special issue on Tabu search
Dynamic tabu list management using the reverse elimination method
Annals of Operations Research - Special issue on Tabu search
Large-scale controlled rounding using tabu search with strategic oscillation
Annals of Operations Research - Special issue on Tabu search
Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
Tabu Search
Near-optimal design of Global Positioning System (GPS) networks using the Tabu Search technique
Journal of Global Optimization
GPS Positioning Networks Design: An Application of the Ant Colony System
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
MMAS and ACS for GPS surveying problem
EC'08 Proceedings of the 9th WSEAS International Conference on Evolutionary Computing
An Heuristic Method for GPS Surveying Problem
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Memetic Simulated Annealing for the GPS Surveying Problem
Numerical Analysis and Its Applications
Hybrid heuristic algorithm for GPS surveying problem
NMA'06 Proceedings of the 6th international conference on Numerical methods and applications
Simulated annealing: a monte carlo method for GPS surveying
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
Hybrid ACO algorithm for the GPS surveying problem
LSSC'09 Proceedings of the 7th international conference on Large-Scale Scientific Computing
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A GPS network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. This paper shows how to search for the best order in which to observe these sessions giving the cheapest schedule. The complexity of observing GPS networks increases with their size and become highly difficult to solve effectively. To obtain good methods to solve this problem a new area of research is implemented. This area is based on developed heuristic techniques that provide an optimal or near optimal solution for large networks. Comparing their outcome in terms of solution quality and computational effort proves the performance of the developed techniques.