{"title":"A cross-layer cooperative optimization framework for optimal scheduling of multi-grade PET fiber production","authors":"Jiale Zhang, Wenli Du, Xin Dai","doi":"10.1016/j.jprocont.2025.103540","DOIUrl":null,"url":null,"abstract":"<div><div>The fluctuations in the supply chain market of polyethylene terephthalate (PET) fibers have been intensifying in recent years. Existing research on the production scheduling of PET plants is usually based on the assumption of a stationary supply chain market. However, these works ignore supply chain fluctuations and market competition, and the schedule obtained may become sub-optimal or infeasible in the real market. This paper considers using the game to represent the competition and cooperation relationships in the market among enterprises with limited supply capacity to obtain equilibrium supplies. Meanwhile, changes in the market prices will cause changes in the equilibrium supplies of the game. In addition, price prediction and supply decisions support the production schedule to achieve high economic efficiency. Therefore, we propose a cross-layer cooperative optimization framework between the supply chain layer and production chain layer for production scheduling optimization. In the supply chain layer, price trends are predicted by synchronous spatio-temporal relationship network, and equilibrium supplies are obtained through a multi-firm multi-product game. In the production chain layer, a production scheduling optimization model that integrates predicted prices and equilibrium supplies from the supply chain layer is established. The effectiveness of the proposed method is verified on a real-world PET plant.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103540"},"PeriodicalIF":3.9000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Process Control","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0959152425001684","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The fluctuations in the supply chain market of polyethylene terephthalate (PET) fibers have been intensifying in recent years. Existing research on the production scheduling of PET plants is usually based on the assumption of a stationary supply chain market. However, these works ignore supply chain fluctuations and market competition, and the schedule obtained may become sub-optimal or infeasible in the real market. This paper considers using the game to represent the competition and cooperation relationships in the market among enterprises with limited supply capacity to obtain equilibrium supplies. Meanwhile, changes in the market prices will cause changes in the equilibrium supplies of the game. In addition, price prediction and supply decisions support the production schedule to achieve high economic efficiency. Therefore, we propose a cross-layer cooperative optimization framework between the supply chain layer and production chain layer for production scheduling optimization. In the supply chain layer, price trends are predicted by synchronous spatio-temporal relationship network, and equilibrium supplies are obtained through a multi-firm multi-product game. In the production chain layer, a production scheduling optimization model that integrates predicted prices and equilibrium supplies from the supply chain layer is established. The effectiveness of the proposed method is verified on a real-world PET plant.
期刊介绍:
This international journal covers the application of control theory, operations research, computer science and engineering principles to the solution of process control problems. In addition to the traditional chemical processing and manufacturing applications, the scope of process control problems involves a wide range of applications that includes energy processes, nano-technology, systems biology, bio-medical engineering, pharmaceutical processing technology, energy storage and conversion, smart grid, and data analytics among others.
Papers on the theory in these areas will also be accepted provided the theoretical contribution is aimed at the application and the development of process control techniques.
Topics covered include:
• Control applications• Process monitoring• Plant-wide control• Process control systems• Control techniques and algorithms• Process modelling and simulation• Design methods
Advanced design methods exclude well established and widely studied traditional design techniques such as PID tuning and its many variants. Applications in fields such as control of automotive engines, machinery and robotics are not deemed suitable unless a clear motivation for the relevance to process control is provided.