{"title":"Adaptive optimal control of the production inventory system in supply chain management with completely unknown dynamics","authors":"F. Mahdizadeh, H. Izadbakhsh","doi":"10.5267/j.msl.2023.6.005","DOIUrl":null,"url":null,"abstract":"This paper describes the adaptive optimal control of the inventory production system with Weibull-distributed deterioration items. First of all, the dynamic model of the system is presented with all possible disturbances and uncertainties. Then, it is controlled using an adaptive and optimal controller. In this method, by having numerical data from the output of the system without using its dynamic equations, an LQR controller is estimated for it. This is important and practical because in physical systems under significant disturbances and fundamental uncertainties, the dynamic equations of the system will not have the former reliability; And it is possible to change the equations of motion by adding any non-linearity so that the conventional controllers will suffer an error. Finally, it is shown that due to the nature of the system and existing uncertainties, the used method has a clear advantage over other optimal control methods and their application in optimizing the inventory production system in the supply chain.","PeriodicalId":30205,"journal":{"name":"Management Science Letters","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Management Science Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5267/j.msl.2023.6.005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper describes the adaptive optimal control of the inventory production system with Weibull-distributed deterioration items. First of all, the dynamic model of the system is presented with all possible disturbances and uncertainties. Then, it is controlled using an adaptive and optimal controller. In this method, by having numerical data from the output of the system without using its dynamic equations, an LQR controller is estimated for it. This is important and practical because in physical systems under significant disturbances and fundamental uncertainties, the dynamic equations of the system will not have the former reliability; And it is possible to change the equations of motion by adding any non-linearity so that the conventional controllers will suffer an error. Finally, it is shown that due to the nature of the system and existing uncertainties, the used method has a clear advantage over other optimal control methods and their application in optimizing the inventory production system in the supply chain.
期刊介绍：
Management Science Letters is a peer reviewed, monthly publication dedicated to create a forum for scientists in all over the world who wish to share their experiences and knowledge in the field of management skills in the form of original, high quality and value added articles. The journal''s policy is to perform a peer review on all submitted articles and the papers will be appeared in a form of online on our website as soon as the review result becomes positive. The journal covers both empirical and theoretical aspects of management and gives the chance on sharing knowledge among practitioners. Management Science Letters is dedicated for publishing in the following areas: • Quality Management • Production Management (Scheduling, Production management, etc.) • Total Quality Management (TQM) • Six Sigma • Production Efficiency • Just in Time Inventory • Data Envelopment Analysis • Balanced Score Card • Activity Based Cost (ABC) • Technology Acceptance Model • Marketing planning and Customer Relationship Management • Critical Success Factors • e-learning • Customer satisfaction, Job satisfaction, Job turnover, • Organizational commitment, Employee Commitment • Knowledge Management • Knowledge sharing • Human Resources Management (Employee training, Employee Performance, Work achievements,) • Small and medium-sized enterprises (SMEs) issues and Economic development • Innovation, Creativity, Productivity and Performance • Multi-Criteria Decision Making Applications in Management Science (AHP, BWM, TOPSIS, …) • Education Management, Social development, Public Policy • Tourism Industry, Tourism promotion, Tourism directorates • Business performance and financial performance
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