Results 201 to 210 of about 729,097 (348)

Dynamic job shop scheduling under multiple order disturbances using deep reinforcement learning. [PDF]

Sci Prog
Sun Z, Han W, Gao L, Zhu C, Lyu Q.
europepmc   +1 more source

Order Management and Completion Date Prediction of Manufacturing Job-Shop Based on Deep Learning.

Comput Intell Neurosci, 2022
Wang M.
europepmc   +1 more source

Dual-resource flexible job shop scheduling considering worker proficiency differences

Chuang Wang, Di Fan, Yang Liu, Shan Ren, Jin Wang   +4 more
openalex   +1 more source

A Hybrid Genetic Algorithm for Multi-Objective Job Shop Scheduling in Manufacturing Systems

, 2023
Thierry Dubois
openalex   +2 more sources

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

An improved scatter search algorithm for solving job shop scheduling problems with parallel batch processing machine. [PDF]

Sci Rep
Wang H, Xiong H, Zuo W, Shi S.
europepmc   +1 more source

A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model. [PDF]

PLoS One, 2020
Tian X, Liu X, Zhang H, Sun M, Zhao Y.
europepmc   +1 more source

Three hybridization models based on local search scheme for job shop scheduling problem [PDF]

, 2015
Tatiana Balbi Fraga
openalex   +1 more source

Efficient Multifunctional Response and Polarization Switching in BiFeO3–PbZr0.58Ti0.42O3–MnFe2O4‐Based Triphasic Composites for Advanced Pulsating Applications

Advanced Engineering Materials, EarlyView.
Triphasic BiFeO3–PbZr0.58Ti0.42O3–MnFe2O4 composites exhibit enhanced ferroelectric and magnetic behavior, achieving 70.76% energy‐storage efficiency and improved polarization switching. The coupling between ferroelectric and magnetic phases enables multifunctional performance, making these composites promising candidates for next‐generation energy ...
Hassan Raza Khan, Muzzamal Hussain, Rabia Baqi, Shahid Ali, Abdulaziz Alhazaa, Muhammad Ali Shar, Ammar Tariq, Shahid Atiq   +7 more
wiley   +1 more source

Data-driven automated job shop scheduling optimization considering AGV obstacle avoidance. [PDF]

Sci Rep
Tang Q, Wang H.
europepmc   +1 more source