Results 41 to 50 of about 3,146 (222)
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Non-convex mixed-integer nonlinear programming : a survey [PDF]
, 2012 A wide range of problems arising in practical applications can be formulated as Mixed-Integer Nonlinear Programs (MINLPs). For the case in which the objective and constraint functions are convex, some quite effective exact and heuristic algorithms are ...
Burer, S +3 more
core
A Global Optimization Algorithm for Signomial Geometric Programming Problem
Abstract and Applied Analysis, 2014 This paper presents a global optimization algorithm for solving the signomial geometric programming (SGP) problem. In the algorithm, by the straight forward algebraic manipulation of terms and by utilizing a transformation of variables, the initial ...
Xue-Ping Hou +2 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas +4 more
wiley +1 more source
A Note on Error Bounds for Convex and Nonconvex Programs [PDF]
Computational Optimization and Applications, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Novel Model for The Energy Minimisation of Natural Gas Transmission Networks
Chemical Engineering Transactions, 2017 Natural gas transmission through an extensive pipeline network is an energy consuming process required gas compression due to significant pressure drop. The main difficulties in optimising a natural gas transmission network are the nonconvexities of the ...
Y. Liang, E. Pahija, C.-W. Hui
doaj +1 more source
Advanced Intelligent Systems, EarlyView.An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
wiley +1 more source
Reformulations of mathematical programming problems as linear complementarity problems [PDF]
, 1982 A family of complementarity problems are defined as extensions of the well known Linear Complementarity Problem (LCP). These are (i.) Second Linear Complementarity Problem (SLCP) which is an LCP extended by introducing further equality restrictions and ...
Mitra, G, Judice, JJ
core
Polyhedral approximation strategies for nonconvex mixed-integer nonlinear programming in SHOT [PDF]
, 2022 Different versions of polyhedral outer approximation are used by many algorithms for mixed-integer nonlinear programming (MINLP). While it has been demonstrated that such methods work well for convex MINLP, extending them to solve nonconvex problems has ...
Lundell, Andreas, Kronqvist, Jan,
core +1 more source