Results 71 to 80 of about 2,313 (260)
Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization
AIChE Journal, EarlyView.Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed +4 more
wiley +1 more source
Vector discrete problems: parametrization of an optimality principle and conditions of solvability in the class of algorithms involving linear convolution of criteria [PDF]
Computer Science Journal of Moldova, 2001 An n-criteria problem with a finite set of vector valuations is considered. An optimality principle of this problem is given by an integer-valued parameter s, which is varied from 1 to n-1.
V.A. Emelichev, A.V. Pashkevich
doaj
Graph‐based imitation and reinforcement learning for efficient Benders decomposition
AIChE Journal, EarlyView.Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman +3 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Trade-off drives Pareto optimality of within- and among-year emergence timing in response to increasing aridity. [PDF]
Evol Appl, 2021 Waterton J +3 more
europepmc +1 more source
Pareto-Optimality in Linear Regression
Journal of Mathematical Analysis and Applications, 1995 In this paper the linear regression problem is studied in the context of vector optimization theory. The set of Pareto-optimal solutions is represented as the set of optimal solutions to certain optimization problems, and is geometrically characterized as a finite union of bounded polyhedra.
Carrizosa Priego, Emilio José +4 more
openaire +3 more sources
Advanced Intelligent Discovery, EarlyView.Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir +4 more
wiley +1 more source
The 80/20 Principle: to use or not to use
RUDN Journal of Economics, 2010 The phenomenon of discovery and usage of Pareto principle phenomenon is considered. Areas of application of this principle (time-management, ABC-analysis, assortment organizing, Pareto-analysis of optimality) is described.
A P Pakhomov
doaj
Pareto-based guaranteed cost control of discrete-time uncertain stochastic systems
Franklin OpenThe Pareto-based guaranteed cost control (GCC) of discrete-time uncertain stochastic systems in the infinite horizon is studied. Firstly, the convexity of the weighted sum objective function is proved.
Xiushan Liang +2 more
doaj +1 more source
The Labor Theory of Value: A Marginal Analysis
World Review of Political Economy, 2014 This article presents the marginal approach to the labor theory of value. The difficulties of the classical and Marxian labor theory of value are overcome when labor value is understood as marginal labor value analogously to marginal cost. Marginal labor
Klaus Hagendorf
doaj +1 more source