Results 71 to 80 of about 3,146 (222)
Stochastic dual dynamic programming applied to nonconvex hydrothermal models [PDF]
, 2012 Artículos en revistasIn this paper we apply stochastic dual dynamic programming decomposition to a nonconvex multistage stochastic hydrothermal model where the nonlinear water head effects on production and the nonlinear dependence between the reservoir ...
Cerisola Lopez De Haro, Santiago +2 more
core +1 more source
The Canadian Journal of Chemical Engineering, Volume 104, Issue 8, Page 4079-4100, August 2026.Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos +3 more
wiley +1 more source
An Interior-Point algorithm for Nonlinear Minimax Problems [PDF]
We present a primal-dual interior-point method for constrained nonlinear, discrete minimax problems where the objective functions and constraints are not necessarily convex.
E. Obasanjo, G. Tzallas-Regas, B. Rustem
core
Technical Note—Bounding Nonconvex Programs by Conjugates [PDF]
Operations Research, 1973 We point out that the Lagrangian dual conjugation in response space provides a stronger bound and requires less computation than conjugate convexification in decision space. A homotopy is then described to lend economic interpretation in the presence of gaps.
openaire +1 more source
Journal of Multi-Criteria Decision Analysis, Volume 33, Issue 2, August 2026.ABSTRACT It is common in many real‐world scenarios for decisions to be made on behalf of others. However, Multicriteria Decision Aiding methods often implicitly assume that the person whose preferences operate the methods, known as the decision‐maker, is the source of those preferences.
Maura E. Halstead +3 more
wiley +1 more source
Nonconvex quadratically constrained quadratic programming: best D.C. decompositions and their SDP representations [PDF]
Nonconvex quadratically constrained quadratic programming, Optimal D.C. decomposition, Semidefinite program, Piecewise linear approximation, Feasible solution,
X. Zheng, X. Sun, D. Li
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Gap inequalities for non-convex mixed-integer quadratic programs [PDF]
, 2011 Laurent and Poljak introduced a very general class of valid linear inequalities, called gap inequalities, for the max-cut problem. We show that an analogous class of inequalities can be defined for general non-convex mixed-integer quadratic programs ...
Galli, Laura +8 more
core +1 more source
Interior-Point Methods for Nonconvex Nonlinear Programming: Complementarity Constraints [PDF]
, 2002 In this paper, we present the formulation and solution of optimization problems with complementarity constraints using an interior-point method for nonconvex nonlinear programming.
Hande Y Benson +2 more
core +2 more sources
MathematicsThe reentry trajectory planning problem of hypersonic vehicles is generally a continuous and nonconvex optimization problem, and it constitutes a critical challenge within the field of aerospace engineering.
Haizhao Liang +4 more
doaj +1 more source
TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks
International Journal of Distributed Sensor Networks, 2015 The time delay of arrival- (TDOA-) based source localization using a wireless sensor network has been considered in this paper. The maximum likelihood estimate (MLE) is formulated by taking the correlated TDOA noise into account, which is caused by the ...
Yongsheng Yan +4 more
doaj +1 more source