2014
DOI: 10.1007/978-1-4614-9093-7
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Simplicial Global Optimization

Abstract: SpringerBriefs in Optimization showcases algorithmic and theoretical techniques, case studies, and applications within the broad-based field of optimization. Manuscripts related to the ever-growing applications of optimization in applied mathematics, engineering, medicine, economics, and other applied sciences are encouraged. This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re… Show more

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Cited by 150 publications
(63 citation statements)
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“…One possible method for solving the fractional programming problem (34) is through simplicity optimization by subdivision of the simplex and using the branch and bound algorithm to find the maximum [3,4,5]. Now let us construct another bound.…”
Section: Methods For Solving the Upper Boundsmentioning
confidence: 99%
See 1 more Smart Citation
“…One possible method for solving the fractional programming problem (34) is through simplicity optimization by subdivision of the simplex and using the branch and bound algorithm to find the maximum [3,4,5]. Now let us construct another bound.…”
Section: Methods For Solving the Upper Boundsmentioning
confidence: 99%
“…That means that the constraint e λ − 1 does not influence the optimum solution for primal problem (1). This is an alternative way to prove there is no gap between problem (1) and problem (3), and therefore no gap between problem (1) and problem (4). Now we derive the relationships of u , λ , and α from stationary condition (6) and complementary condition (7).…”
Section: A Surrogate Optimization Model Of the Contact Problemmentioning
confidence: 99%
“…These constraints were taken into account in the optimization task by the external penalty function [25,26], of which value was added to the objective function minimized:…”
Section: Optimisation Problemmentioning
confidence: 99%
“…A Branch and Bound (B&B) algorithm is a commonly-used method to solve Global Optimization (GO) problems in a deterministic way [20,26,27,38]. This method iteratively divides the search space and discards those areas where a global solution cannot be found.…”
Section: Introductionmentioning
confidence: 99%