2016
DOI: 10.1007/978-3-319-31484-6_11
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Monotonic Optimization

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Cited by 3 publications
(9 citation statements)
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“…Nevertheless, we remark that the complexity of monotonic optimization methods is still exponential in the number of variables. However, as already observed, it is much lower than general global optimization methods, which do not exploit any monotonicity structure [21]. This makes monotonic optimization attractive for the development of an off-line framework to benchmark any suboptimal method for solving (24).…”
Section: B Monotonic Optimizationmentioning
confidence: 98%
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“…Nevertheless, we remark that the complexity of monotonic optimization methods is still exponential in the number of variables. However, as already observed, it is much lower than general global optimization methods, which do not exploit any monotonicity structure [21]. This makes monotonic optimization attractive for the development of an off-line framework to benchmark any suboptimal method for solving (24).…”
Section: B Monotonic Optimizationmentioning
confidence: 98%
“…This optimization framework can solve optimization problems where the utility and constraints are monotonically increasing/decreasing functions of the variables, even if no convexity assumption is fulfilled. The polyblock algorithm [21] and the branch-reduce-and-bound (BRB) algorithm [22] are two key algorithms for globally solving these problems. These algorithms have recently been used to solve different non-convex problems in communication and networking systems; for example, joint power control and scheduling [23] and sum rate maximization with multi-antenna transmitters [24].…”
Section: A State-of-the-artmentioning
confidence: 99%
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