Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3455691
{"title":"IEEE Systems, Man, and Cybernetics Society Information","authors":"","doi":"10.1109/TSMC.2024.3455691","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3455691","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"54 10","pages":"C3-C3"},"PeriodicalIF":8.6,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10682094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142235844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3455653
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Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3455649
{"title":"IEEE Transactions on Systems, Man, and Cybernetics publication information","authors":"","doi":"10.1109/TSMC.2024.3455649","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3455649","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"54 10","pages":"C2-C2"},"PeriodicalIF":8.6,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10682075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142246488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3455689
{"title":"IEEE Transactions on Systems, Man, and Cybernetics publication information","authors":"","doi":"10.1109/TSMC.2024.3455689","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3455689","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"54 10","pages":"C2-C2"},"PeriodicalIF":8.6,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10682081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3450126
Shuyu Zhang;Xiao-Dong Li;Xuefang Li
In this work, a novel event-triggered iterative learning model predictive control (ILMPC) framework is developed for a class of linear systems subject to input saturation and initial shift. First, a nominal ILMPC strategy is proposed to clearly demonstrate the design philosophy, in which an initial state learning scheme is incorporated to remove the identical initialization condition. Furthermore, in order to reduce the communication and computation loads of the proposed ILMPC approach, two efficient ILMPC strategies, namely, a time-direction event-triggered ILMPC and a hybrid time-iteration-direction event-triggered ILMPC schemes, are developed by considering the event-triggered strategies along the time and iteration axes. It is shown that the proposed event-triggered ILMPC strategies are able to save the communication and computation resources significantly while maintaining the tracking control performance. The convergence of the proposed ILMPC schemes are analyzed rigorously via the contraction mapping methodology and the Lyapunov-like theory, and the effectiveness of the proposed ILMPC method is verified through a numerical example.
{"title":"A Novel Event-Triggered Iterative Learning Model Predictive Control for Linear Systems","authors":"Shuyu Zhang;Xiao-Dong Li;Xuefang Li","doi":"10.1109/TSMC.2024.3450126","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3450126","url":null,"abstract":"In this work, a novel event-triggered iterative learning model predictive control (ILMPC) framework is developed for a class of linear systems subject to input saturation and initial shift. First, a nominal ILMPC strategy is proposed to clearly demonstrate the design philosophy, in which an initial state learning scheme is incorporated to remove the identical initialization condition. Furthermore, in order to reduce the communication and computation loads of the proposed ILMPC approach, two efficient ILMPC strategies, namely, a time-direction event-triggered ILMPC and a hybrid time-iteration-direction event-triggered ILMPC schemes, are developed by considering the event-triggered strategies along the time and iteration axes. It is shown that the proposed event-triggered ILMPC strategies are able to save the communication and computation resources significantly while maintaining the tracking control performance. The convergence of the proposed ILMPC schemes are analyzed rigorously via the contraction mapping methodology and the Lyapunov-like theory, and the effectiveness of the proposed ILMPC method is verified through a numerical example.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"54 12","pages":"7619-7632"},"PeriodicalIF":8.6,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3414832
Anis Yazidi;Hugo Hammer;David S. Leslie
In this article, we introduce a novel learning automata (LA) solution to the nonlinear stochastic proportional polling (NSPP) problem. The only available solution to this problem in the literature is that given by Nicopolitidis et al. (2003), Obaidat et al. (2002), and Papadimitriou et al. (2002). It was shown to solve a large set of the adaptive resource allocation problems under noisy environments (Nicopolitidis et al., 2003; Obaidat et al., 2002; Papadimitriou and Pomportsis, 2000 and 1999; Nicopolitidis et al., 2004; Obaidat et al., 2001; and Papadimitriou and Pomportsis, 2000). We make a threefold contribution. First, we take a two-timescale approach to the field of LA by estimating the reward probabilities on a faster timescale than the timescale for updating the polling probabilities. Second, by making a not-obvious choice of the objective function, we show that the NSPP problem is indeed an instantiation of the stochastic nonlinear fractional equality knapsack (NFEK) problem, which is a substantial resource allocation problem based on the incomplete and noisy information (Granmo and Oommen, 2010). Third, in contrast to the legacy approach taken by Papadimitriou and Maritsas (1992 and 1996), we show through the extensive experimental results that our solution is remarkably robust to the choice of tuning parameters and that it outperforms the state of the art solution in terms of the Bayesian expected loss.
{"title":"A Two-Timescale Learning Automata Solution to the Nonlinear Stochastic Proportional Polling Problem","authors":"Anis Yazidi;Hugo Hammer;David S. Leslie","doi":"10.1109/TSMC.2024.3414832","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3414832","url":null,"abstract":"In this article, we introduce a novel learning automata (LA) solution to the nonlinear stochastic proportional polling (NSPP) problem. The only available solution to this problem in the literature is that given by Nicopolitidis et al. (2003), Obaidat et al. (2002), and Papadimitriou et al. (2002). It was shown to solve a large set of the adaptive resource allocation problems under noisy environments (Nicopolitidis et al., 2003; Obaidat et al., 2002; Papadimitriou and Pomportsis, 2000 and 1999; Nicopolitidis et al., 2004; Obaidat et al., 2001; and Papadimitriou and Pomportsis, 2000). We make a threefold contribution. First, we take a two-timescale approach to the field of LA by estimating the reward probabilities on a faster timescale than the timescale for updating the polling probabilities. Second, by making a not-obvious choice of the objective function, we show that the NSPP problem is indeed an instantiation of the stochastic nonlinear fractional equality knapsack (NFEK) problem, which is a substantial resource allocation problem based on the incomplete and noisy information (Granmo and Oommen, 2010). Third, in contrast to the legacy approach taken by Papadimitriou and Maritsas (1992 and 1996), we show through the extensive experimental results that our solution is remarkably robust to the choice of tuning parameters and that it outperforms the state of the art solution in terms of the Bayesian expected loss.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"54 12","pages":"7158-7169"},"PeriodicalIF":8.6,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3450522
Beatrice Ietto;Valentina Orsini
For a deeper insight on the inventory control problem of periodically reviewed perishable supply chains (SCs) with perishable goods, we here introduce the notion of internal dynamics (ID) and propose a min-max model predictive control (MPC) of the inventory level based on this notion. The acronym ID denotes the actual scheduling of the usual management operations (OPs) executed inside each review period. We show that the information carried by the ID is fundamental to define an efficient inventory control policy (ICP). The notion of ID is particularly important in the case of SCs characterized by elements of complexity like: 1) perishable goods with large, not exactly known deterioration rate; 2) the length of the review period is such as to produce a high spoilage within it; 3) an uncertain future customer demand with oscillations that are not statistically modelable. Exploiting the notion of ID, we define an inventory model properly capturing these features. This model encompasses as particular cases other SC models proposed in the literature. We also define a coherent two criteria-based evaluation of the bullwhip effect (BE). We also provide key managerial insights for a proper scheduling of all the OPs inside each review period. The reported numerical simulations show the effectiveness of our approach.
为了深入探讨易腐物品定期检查供应链(SC)的库存控制问题,我们在此引入了内部动态(ID)的概念,并在此基础上提出了库存水平的最小-最大模型预测控制(MPC)。缩写 ID 表示在每个回顾期内执行的常规管理操作 (OP) 的实际调度。我们表明,ID 所携带的信息是定义高效库存控制策略 (ICP) 的基础。ID 的概念对于具有以下复杂因素的 SC 尤为重要:1) 易腐烂货物的变质率高,且不完全可知;2) 审查期的长度会在审查期内产生较高的变质率;3) 不确定的未来客户需求,且其波动无法用统计学模型来模拟。利用 "ID "概念,我们定义了一个库存模型,该模型能恰当地捕捉这些特征。该模型包括文献中提出的其他 SC 模型。我们还定义了一种基于两个标准的牛鞭效应(BE)评估方法。我们还提供了关键的管理见解,以便在每个审查期内对所有 OP 进行合理安排。报告中的数值模拟显示了我们方法的有效性。
{"title":"The Notion of Internal Dynamics and Its Impact on Modeling and Controlling Supply Chains With Goods Characterized by Uncertain Perishability Rate","authors":"Beatrice Ietto;Valentina Orsini","doi":"10.1109/TSMC.2024.3450522","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3450522","url":null,"abstract":"For a deeper insight on the inventory control problem of periodically reviewed perishable supply chains (SCs) with perishable goods, we here introduce the notion of internal dynamics (ID) and propose a min-max model predictive control (MPC) of the inventory level based on this notion. The acronym ID denotes the actual scheduling of the usual management operations (OPs) executed inside each review period. We show that the information carried by the ID is fundamental to define an efficient inventory control policy (ICP). The notion of ID is particularly important in the case of SCs characterized by elements of complexity like: 1) perishable goods with large, not exactly known deterioration rate; 2) the length of the review period is such as to produce a high spoilage within it; 3) an uncertain future customer demand with oscillations that are not statistically modelable. Exploiting the notion of ID, we define an inventory model properly capturing these features. This model encompasses as particular cases other SC models proposed in the literature. We also define a coherent two criteria-based evaluation of the bullwhip effect (BE). We also provide key managerial insights for a proper scheduling of all the OPs inside each review period. The reported numerical simulations show the effectiveness of our approach.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"54 12","pages":"7356-7368"},"PeriodicalIF":8.6,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10681456","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3455651
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Different from conventional decision-making environments, decision makers (DMs) in a community setting usually exhibit the complex social preferences and intricate social interactions, which may lead to high-decision costs for group consensus reaching. To address this challenge, we design a minimum cost consensus-based social network group decision making (SNGDM) approach considering altruism-fairness preferences and ordered trust propagation. First, a trust propagation method with order effect and path length is proposed to estimate the completed trust relationships among DMs in order to determine the weights of DMs. Then, inspired by the interaction of altruism and fairness preferences, we define the individual altruism-fairness preference utility function and utility level for cost consensus, and explore some properties. Afterwards, a new minimum cost consensus-based SNGDM with individual altruism-fairness preference utility is constructed. Finally, the validity of the proposed consensus framework is confirmed through the carbon reduction consensus problem of China’s aviation enterprises. Moreover, the sensitivity studies and comparative analysis are conducted to further demonstrate the merits of our proposal.
{"title":"Minimum Cost Consensus-Based Social Network Group Decision Making With Altruism-Fairness Preferences and Ordered Trust Propagation","authors":"Yu Feng;Yaoguo Dang;Junjie Wang;Junliang Du;Francisco Chiclana","doi":"10.1109/TSMC.2024.3452931","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3452931","url":null,"abstract":"Different from conventional decision-making environments, decision makers (DMs) in a community setting usually exhibit the complex social preferences and intricate social interactions, which may lead to high-decision costs for group consensus reaching. To address this challenge, we design a minimum cost consensus-based social network group decision making (SNGDM) approach considering altruism-fairness preferences and ordered trust propagation. First, a trust propagation method with order effect and path length is proposed to estimate the completed trust relationships among DMs in order to determine the weights of DMs. Then, inspired by the interaction of altruism and fairness preferences, we define the individual altruism-fairness preference utility function and utility level for cost consensus, and explore some properties. Afterwards, a new minimum cost consensus-based SNGDM with individual altruism-fairness preference utility is constructed. Finally, the validity of the proposed consensus framework is confirmed through the carbon reduction consensus problem of China’s aviation enterprises. Moreover, the sensitivity studies and comparative analysis are conducted to further demonstrate the merits of our proposal.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"54 12","pages":"7605-7618"},"PeriodicalIF":8.6,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1109/TSMC.2024.3455693
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