Integer and combinatorial optimization
Integer and combinatorial optimization
Formulating the single machine sequencing problem with release dates as a mixed integer program
Discrete Applied Mathematics - Southampton conference on combinatorial optimization, April 1987
Valid inequalities for 0–1 knapsacks and mips with generalised upper bound constraints
Selected papers on First international colloquium on pseudo-boolean optimization and related topics
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Base Station Location and Service Assignments in W--CDMA Networks
INFORMS Journal on Computing
Optimisation models for GSM radio
International Journal of Mobile Network Design and Innovation
Optimal routing and resource allocation in multi-hop wireless networks
Optimization Methods & Software - Mathematical programming in data mining and machine learning
Wireless Network Design: Optimization Models and Solution Procedures
Wireless Network Design: Optimization Models and Solution Procedures
Planning wireless networks by shortest path
Computational Optimization and Applications
Automated optimization of service coverage and base station antenna configuration in UMTS networks
IEEE Wireless Communications
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We propose a pure 0-1 formulation for the wireless network design problem, i.e., the problem of configuring a set of transmitters to provide service coverage to a set of receivers. In contrast with classical mixed-integer formulations, where power emissions are represented by continuous variables, we consider only a finite set of power values. This has two major advantages: it better fits the usual practice and eliminates the sources of numerical problems that heavily affect continuous models. A crucial ingredient of our approach is an effective basic formulation for the single knapsack problem representing the coverage condition of a receiver. This formulation is based on the generalized upper bound GUB cover inequalities introduced by Wolsey [Wolsey L 1990 Valid inequalities for 0-1 knapsacks and mips with generalised upper bound constraints. Discrete Appl. Math. 292--3:251--261]; and its core is an extension of the exact formulation of the GUB knapsack polytope with two GUB constraints. This special case corresponds to the very common practical situation where only one major interferer is present. We assess the effectiveness of our formulation by comprehensive computational results over realistic instances of two typical technologies, namely, WiMAX and DVB-T. This paper was accepted by Dimitris Bertsimas, optimization.