Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Simulated annealing: theory and applications
Simulated annealing: theory and applications
Automatic layout of analog and digital mixed macro/standard cell integrated circuits
Automatic layout of analog and digital mixed macro/standard cell integrated circuits
An efficient simulated annealing schedule
An efficient simulated annealing schedule
Learning evaluation functions for global optimization
Learning evaluation functions for global optimization
Uplink UMTS network design: an integrated approach
Computer Networks: The International Journal of Computer and Telecommunications Networking
An effective two-stage simulated annealing algorithm for the minimum linear arrangement problem
Computers and Operations Research
Topological planning and design of UMTS mobile networks: a survey
Wireless Communications & Mobile Computing
Measurement-Based optimization of a 3g core network: a case study
NEW2AN'06 Proceedings of the 6th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking
Planning reliable UMTS terrestrial access networks
IEEE Communications Magazine
Comparison of different meta-heuristics to solve the global planning problem of UMTS networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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In this paper, a simulated annealing algorithm is proposed and studied in order to find "good" feasible solution for the global topology planning problem of Universal Mobile Telecommunications System (UMTS) networks. The latter has been shown to be NP-hard as it is composed of three different subproblems (each one being NP-hard): the cell planning problem, the access network planning problem and the core network planning problem. As a result, we concentrate our effort on the development of an approximate algorithm based on simulated annealing. Numerical results show that quasi-optimal solutions (on average, within 5.26% of the optimal solution) can be found with a relatively short computation time compared to CPLEX.