1992
DOI: 10.1007/bf02238641
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On global optimization using interval arithmetic

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Cited by 10 publications
(9 citation statements)
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“…Closer bounds for the interval function can be found using a branch and bound technique [21][22][23][24]. The bounds of the interval valued function can be found using the interval arithmetic rules combined with a branch and bound technique which splits boxes adaptively until the overestimation becomes insignificant.…”
Section: Lower and Upper Bounds Estimation Of Interval Valued Functionmentioning
confidence: 99%
See 1 more Smart Citation
“…Closer bounds for the interval function can be found using a branch and bound technique [21][22][23][24]. The bounds of the interval valued function can be found using the interval arithmetic rules combined with a branch and bound technique which splits boxes adaptively until the overestimation becomes insignificant.…”
Section: Lower and Upper Bounds Estimation Of Interval Valued Functionmentioning
confidence: 99%
“…If it is linear, it can be solved easily by inequality constrained linear programming approach. In case of nonlinear interval valued functions, the bounds can be estimated from the methods addressed in the literature [21][22][23][24].…”
Section: Lower and Upper Bounds Estimation Of Interval Valued Functionmentioning
confidence: 99%
“…It is easy to observe that: Nowadays, interval arithmetic has been widely applied to many scientific fields, see [17][18][19][20][21]. For example, interval arithmetic is helpful in solving polynomial equations system.…”
Section: Interval Arithmetic and Interval Polynomialmentioning
confidence: 99%
“…We have used the branch and bound (BnB) technique to solve the priority-aware expected weighted goodput optimization problem [43][44][45]. BnB is a global optimization technique used for non-convex problems, especially in discrete and combinatorial optimization.…”
Section: Priority-aware Fragmentationmentioning
confidence: 99%
“…The Branch and Bound (BnB) algorithm along with an interval arithmetic method [43][44][45] is used to find the maximum expected weighted goodput and derive the optimal fragment sizes. In order to reduce error propagation within a group of pictures (GOP), we use a slice discard scheme based on frame importance and the cumulative mean square error (CMSE) contribution of the slice.…”
Section: Uep Performancementioning
confidence: 99%