Results 61 to 70 of about 26,837 (219)

Shaping Decision Models for Stochastic Dynamic Optimization Problems via Reinforcement Learning

Networks, EarlyView.
ABSTRACT With rising customer expectations and increasing computational potential, many transport, manufacturing, and production operations face real‐time decision making in stochastic dynamic environments. Decision makers must find and adapt complex plans that are effective now but also flexible with respect to future developments.
Florentin D. Hildebrandt, Alexander Bode, Marlin W. Ulmer, Dirk C. Mattfeld   +3 more
wiley   +1 more source

Interdiction Models and Heuristics for Graph Propagation

Networks, EarlyView.
ABSTRACT Given a graph G=(V,E)$$ G=\left(V,E\right) $$ and a set S⊂V$$ S\subset V $$ of activated/infected nodes, we consider the problem of determining the set of c$$ c $$ nodes that minimizes the network propagation on the subgraph that results from the removal of those c$$ c $$ nodes. To measure network propagation, we assume that a node i$$ i $$ is
Agostinho Agra, José Maria Samuco
wiley   +1 more source

Research on the placement algorithm of two-tiered constrained relay nodes in wireless sensor networks

上海师范大学学报. 自然科学版, 2017
In three-dimensional space,when the location of relay nodes is limited and it is a two-layer topology,a relay location algorithm based on mixed integer linear programming (MILP) is proposed.The algorithm first considers the physical layer model placed by
Xiang Haokai, Zhou Xiaoping, Wang Jianan, Li Li, Huang Jiahui   +4 more
doaj   +1 more source

An Extended Model for the UAVs-Assisted Multiperiodic Crowd Tracking Problem

Complexity, 2023
The multiperiodic crowd tracking (MPCT) problem is an extension of the periodic crowd tracking (PCT) problem, recently addressed in the literature and solved using an iterative solver called PCTs solver.
Skander Htiouech, Khalil Chebil, Mahdi Khemakhem, Fidaa Abed, Monaji H. Alkiani   +4 more
doaj   +1 more source

Advancing the Thermal Network Representation for the Optimal Design of Distributed Multi-Energy Systems

Frontiers in Energy Research, 2021
This paper investigates modeling methods with thermal network representation under the scope of the optimal design and operation of Distributed Multi-Energy System (D-MES).
Danhong Wang, Danhong Wang, Xiang Li, Julien Marquant, Julien Marquant, Jan Carmeliet, Kristina Orehounig   +6 more
doaj   +1 more source

Polyhedral approximation in mixed-integer convex optimization

, 2017
Generalizing both mixed-integer linear optimization and convex optimization, mixed-integer convex optimization possesses broad modeling power but has seen relatively few advances in general-purpose solvers in recent years.
Bent, Russell, Lubin, Miles, Vielma, Juan Pablo, Yamangil, Emre   +3 more
core   +1 more source

Cost‐Optimal Building Energy System Scheduling Integrating Solar Irradiance Forecasting via LSTM‐Attention‐TCN Model

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Building energy systems integrating multiple energy sources can effectively reduce energy consumption and facilitate renewable energy integration. Integrating electrical energy storage (EES) into these systems helps accommodate the increasing share of renewables; however, the stochastic and intermittent nature of solar power still poses ...
Zhengtian Wu, Jianyu Li, Yang Gao, Chuangyin Dang, Chao Tang, Yuansheng Li, Xinmiao Wang, Jinpeng Chen, Hongbo Gao, Xinyin Xu   +9 more
wiley   +1 more source

Minimizing the makespan and carbon emissions in the green flexible job shop scheduling problem with learning effects

Scientific Reports, 2023
One of the most difficult challenges for modern manufacturing is reducing carbon emissions. This paper focuses on the green scheduling problem in a flexible job shop system, taking into account energy consumption and worker learning effects.
Zhi Li, Yingjian Chen
doaj   +1 more source

Converting of Boolean Expression to Linear Equations, Inequalities and QUBO Penalties for Cryptanalysis

Algorithms, 2022
There exists a wide range of constraint programming (CP) problems defined on Boolean functions depending on binary variables. One of the approaches to solving CP problems is using specific appropriate solvers, e.g., SAT solvers.
Aleksey I. Pakhomchik, Vladimir V. Voloshinov, Valerii M. Vinokur, Gordey B. Lesovik   +3 more
doaj   +1 more source

Empirical Bounds on Linear Regions of Deep Rectifier Networks

, 2019
We can compare the expressiveness of neural networks that use rectified linear units (ReLUs) by the number of linear regions, which reflect the number of pieces of the piecewise linear functions modeled by such networks.
Ramalingam, Srikumar, Serra, Thiago
core   +1 more source