Results 241 to 250 of about 11,997,994 (262)

Expensive Inequality Constraints Handling Methods Suitable for Dynamic Surrogate-based Optimization

2019 IEEE Congress on Evolutionary Computation (CEC), 2019
In modern engineering design optimization problems, high-fidelity analyses are always used for evaluating objectives and constraints, which might be quite expensive. Thus, efficient global optimization method should be developed to relieve the computational burden.
Chunna Li, Hai Fang, Chunlin Gong
openaire   +3 more sources

A block-iterative surrogate constraint splitting method for quadratic signal recovery

IEEE Transactions on Signal Processing, 2003
A block-iterative parallel decomposition method is proposed to solve general quadratic signal recovery problems under convex constraints. The proposed method proceeds by local linearizations of blocks of constraints, and it is therefore not sensitive to their analytical complexity.
P L Combettes
openaire   +4 more sources

Advanced greedy algorithms and surrogate constraint methods for linear and quadratic knapsack and covering problems

European Journal of Operational Research, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fred W. Glover
openaire   +5 more sources

Surrogate Based Method for Evaluation of Failure Probability under Multiple Constraints

SIAM Journal on Scientific Computing, 2014
In this paper we study the problem of computing failure probability subject to multiple constraints. In particular, we consider the case of surrogate models, also known as response surfaces, for the available constraints. An important feature is that the surrogates are not required to have high accuracy.
Jing Li, Dongbin Xiu
openaire   +2 more sources

Surrogate Constraint Methods for Linear Inequalities

1992
Systems of linear inequalities and equations are very important in optimization. Recent applications of mathematical programming in areas such as computerized tomography (CAT scan) lead to very large and sparse systems of linear equations and inequalities which need to be solved approximately within reasonable time.
Kai Yang, Katta G. Murty
openaire   +1 more source

Solving the Redundancy Allocation Problem With a Mix of Components Using the Improved Surrogate Constraint Method

IEEE Transactions on Reliability, 2007
When designing a system, there are two methods that can be used to improve the system's reliability without changing the nature of the system: 1) using more reliable components, and/or 2) providing redundant components within the system. The redundancy allocation problem attempts to find the appropriate mix of components & redundancies within a system ...
J. Onishi, S. Kimura, Ross J. W. James, Yuji Nakagawa   +3 more
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Asymptotic surrogate constraint method and its convergence for a class of semi-infinite programming

Applied Mathematics-A Journal of Chinese Universities, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wan, Zhongping, Wu, Guoming
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Optimal design problems of highly reliable systems and their solution methods by surrogate constraints algorithm

Electronics and Communications in Japan (Part I: Communications), 1988
AbstractThis paper presents a solution method for the reliability optimization problem of systems which is formulated as a mixed‐integer nonlinear programming problem with multiple constraints. The system structure is series, series‐parallel, or complex.
Mitsunori Hikita, Yuji Nakagawa, Kyoichi Nakashima, Kazuharu Yamato   +3 more
openaire   +1 more source

Convergence of the Projected Surrogate Constraints Method for the Linear Split Feasibility Problems

Journal of Convex Analysis, 2007
The surrogate constraints method (SC-method) for linear feasibility problems (LFP) is an important tool in convex optimization, especially in large scale optimization. The classical version of the SC-method converges to a solution if the LFP is feasible [see K. Yang and K. G. Murty, J. Optim. Theory Appl. 72 (1992) 163–185].
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An efficient surrogate optimization method for solving linear mixed-integer problems with cross-coupling constraints

Proceedings of the 10th World Congress on Intelligent Control and Automation, 2012
Many optimization problems that frequently arise and have been extensively used in practice are modeled as linear mixed-integer programming problems. Among the many of such problems are transportation and assignment problems. In such problems, constraints that couple decision variables can be viewed as hyperplanes in their respective spaces.
Mikhail A. Bragin, Peter B. Luh, Joseph H. Yan   +2 more
openaire   +1 more source