Production Scheduling Optimization enabled by Digital Cognitive Platform

Author:

Georgiadis Konstantinos,Nizamis Alexandros,Vafeiadis Thanasis,Ioannidis Dimosthenis,Tzovaras Dimitrios

Funder

Horizon 2020 Framework Programme

Horizon 2020

Publisher

Elsevier BV

Subject

General Engineering

Reference18 articles.

1. A research survey: review of flexible job shop scheduling techniques;Chaudhry;International Transactions in Operational Research,2016

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3. Multiobjective evolutionary algorithm for manufacturing scheduling problems: state-of-the-art survey;Gen;Journal of Intelligent Manufacturing,2014

4. Modified genetic algorithm for employee work shifts scheduling optimization;Saraswati;Journal of Physics: Conference Series,2020

5. Maintenance Scheduling Optimization Using a Genetic Algorithm (GA) with a Probabilistic Fitness Function;ABDULWHAB;Electric Power Components and Systems,2010

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1. Enhancing manufacturing operations with synthetic data: a systematic framework for data generation, accuracy, and utility;Frontiers in Manufacturing Technology;2024-02-13

2. Machine learning-driven optimization of enterprise resource planning (ERP) systems: a comprehensive review;Beni-Suef University Journal of Basic and Applied Sciences;2024-01-04

3. A Holistic Framework for Production Scheduling in Industry 4.0;2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT);2023-06

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