Next Article in Journal
Learning Output Reference Model Tracking for Higher-Order Nonlinear Systems with Unknown Dynamics
Previous Article in Journal
The Role of Façade Materials in Blast-Resistant Buildings: An Evaluation Based on Fuzzy Delphi and Fuzzy EDAS
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle

Integration of Production Planning and Scheduling Based on RTN Representation under Uncertainties

1, 1,2,*, 1,2 and 3
1
School of Information and Control Engineering, Liaoning Shihua University, Fushun 113001, China
2
National Experimental Teaching Demonstration Center of Petrochemical Process Control, Liaoning Shihua University, Fushun 113001, China
3
Institute of Intelligence Science and Engineering, Shenzhen Polytechnic, Shenzhen 518055, China
*
Author to whom correspondence should be addressed.
Algorithms 2019, 12(6), 120; https://doi.org/10.3390/a12060120
Received: 19 April 2019 / Revised: 2 June 2019 / Accepted: 6 June 2019 / Published: 10 June 2019
  |  
PDF [2984 KB, uploaded 26 June 2019]
  |  

Abstract

Production planning and scheduling are important bases for production decisions. Concerning the traditional modeling of production planning and scheduling based on Resource-Task Network (RTN) representation, uncertain factors such as utilities are rarely considered as constraints. For the production planning and scheduling problem based on RTN representation in an uncertain environment, this paper formulates the multi-period bi-level integrated model of planning and scheduling, and introduces the uncertainties of demand and utility in planning and scheduling layers respectively. Rolling horizon optimization strategy is utilized to solve the bi-level integrated model iteratively. The simulation results show that the proposed model and algorithm are feasible and effective, can calculate the consumption of utility in every period, decrease the effects of uncertain factors on optimization results, more accurately describe the uncertain factors, and reflect the actual production process. View Full-Text
Keywords: production planning and scheduling; RTN representation; integration model; uncertainties production planning and scheduling; RTN representation; integration model; uncertainties
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Zhang, T.; Wang, Y.; Jin, X.; Lu, S. Integration of Production Planning and Scheduling Based on RTN Representation under Uncertainties. Algorithms 2019, 12, 120.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top