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SNOPT: An SQP Algorithm For LargeScale Constrained Optimization
, 2002
"... Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first deriv ..."
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Cited by 582 (23 self)
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Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first
Constraint Networks
, 1992
"... Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint expression ..."
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Cited by 1149 (43 self)
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expressions. These have been successfully applied to diverse tasks such as design, diagnosis, truth maintenance, scheduling, spatiotemporal reasoning, logic programming and user interface. Constraint networks are graphical representations used to guide strategies for solving constraint satisfaction problems
Analogical Mapping by Constraint Satisfaction
 COGNITIVE SCIENCE 13, 295 (1989)
, 1989
"... A theory of analogical mopping between source and target analogs based upon interacting structural, semantic, and pragmatic constraints is proposed here. The structural constraint of fsomorphfsm encourages mappings that maximize the consistency of relational corresondences between the elements of th ..."
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Cited by 389 (28 self)
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the anology Is being used. The theory is implemented in a computer progrom called ACME (Analogical Constraint Mapping Engine), which represents constraints by means of a network of supporting and competing hypotheses regarding what elements to map. A coop erative algorithm for parallel constraint satisfaction
Constrained model predictive control: Stability and optimality
 AUTOMATICA
, 2000
"... Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon openloop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence and t ..."
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Cited by 696 (15 self)
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Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon openloop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence
Prosodic Morphology: constraint interaction and satisfaction
, 1993
"... Permission is hereby granted by the authors to reproduce this document, in whole or in part, for personal use, for instruction, or for any other noncommercial purpose. Table of Contents Acknowledgments......................................................... ..."
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Cited by 420 (31 self)
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Permission is hereby granted by the authors to reproduce this document, in whole or in part, for personal use, for instruction, or for any other noncommercial purpose. Table of Contents Acknowledgments.........................................................
Satisfaction and Comparison Income
 Journal of Public Economics
, 1995
"... This paper is an attempt to test the hypothesis that utility depends on income relative to a 'comparison' or reference level. Using data on 5,000 British workers, it provides two findings. First, workers' reported satisfaction levels are shown to be inversely related to their comparis ..."
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Cited by 616 (55 self)
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This paper is an attempt to test the hypothesis that utility depends on income relative to a 'comparison' or reference level. Using data on 5,000 British workers, it provides two findings. First, workers' reported satisfaction levels are shown to be inversely related
An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
, 2008
"... ..."
A Limited Memory Algorithm for Bound Constrained Optimization
 SIAM Journal on Scientific Computing
, 1994
"... An algorithm for solving large nonlinear optimization problems with simple bounds is described. ..."
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Cited by 557 (9 self)
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An algorithm for solving large nonlinear optimization problems with simple bounds is described.
Concurrent Constraint Programming
, 1993
"... This paper presents a new and very rich class of (concurrent) programming languages, based on the notion of comput.ing with parhal information, and the concommitant notions of consistency and entailment. ’ In this framework, computation emerges from the interaction of concurrently executing agent ..."
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Cited by 502 (16 self)
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agents that communicate by placing, checking and instantiating constraints on shared variables. Such a view of computation is interesting in the context of programming languages because of the ability to represent and manipulate partial information about the domain of discourse, in the con
Constraint Logic Programming: A Survey
"... Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Although a relatively new field, CLP has progressed in several quite different directions. In particular, the early fundamental concepts have been adapted to better serve in differe ..."
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Cited by 864 (25 self)
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Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Although a relatively new field, CLP has progressed in several quite different directions. In particular, the early fundamental concepts have been adapted to better serve
Results 1  10
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1,398,214