{"title":"不确定环境下可靠性依赖不完全生产库存最优控制分数阶模型","authors":"S. Hati, K. Maity","doi":"10.1080/16168658.2022.2152885","DOIUrl":null,"url":null,"abstract":"ABSTRACT In this paper, we present a general formulation for the production inventory optimal control problem to a class of fractional fuzzy differential systems with reliability-dependent imperfect production. we investigate this model under the uncertain environment of fuzzy numbers with the rate of change of stock level expressed by granular Caputo fractional fuzzy derivative of order . The demands depend on the selling price, product quality, and stock level of the product displayed in the store. The unit production cost depends on development cost due to reliability, raw material cost, and wear tear cost. Here state, co-state variables and parameters are taken as uncertain variables with triangular fuzzy numbers and using granular dierentiability the existence and uniqueness of solution to the fractional dierential system with fuzzy variables and parameters. The production inventory optimal control problem for the fractional system is proposed and a necessary condition for optimality is obtained. Finally, this optimal control problem was solved by using the Pontryagin Maximum principle and for numerical results and graphical representation.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"294 1","pages":"379 - 406"},"PeriodicalIF":1.3000,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Reliability Dependent Imperfect Production Inventory Optimal Control Fractional Order Model for Uncertain Environment Under Granular Differentiability\",\"authors\":\"S. Hati, K. Maity\",\"doi\":\"10.1080/16168658.2022.2152885\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT In this paper, we present a general formulation for the production inventory optimal control problem to a class of fractional fuzzy differential systems with reliability-dependent imperfect production. we investigate this model under the uncertain environment of fuzzy numbers with the rate of change of stock level expressed by granular Caputo fractional fuzzy derivative of order . The demands depend on the selling price, product quality, and stock level of the product displayed in the store. The unit production cost depends on development cost due to reliability, raw material cost, and wear tear cost. Here state, co-state variables and parameters are taken as uncertain variables with triangular fuzzy numbers and using granular dierentiability the existence and uniqueness of solution to the fractional dierential system with fuzzy variables and parameters. The production inventory optimal control problem for the fractional system is proposed and a necessary condition for optimality is obtained. Finally, this optimal control problem was solved by using the Pontryagin Maximum principle and for numerical results and graphical representation.\",\"PeriodicalId\":37623,\"journal\":{\"name\":\"Fuzzy Information and Engineering\",\"volume\":\"294 1\",\"pages\":\"379 - 406\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2022-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fuzzy Information and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/16168658.2022.2152885\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fuzzy Information and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/16168658.2022.2152885","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Reliability Dependent Imperfect Production Inventory Optimal Control Fractional Order Model for Uncertain Environment Under Granular Differentiability
ABSTRACT In this paper, we present a general formulation for the production inventory optimal control problem to a class of fractional fuzzy differential systems with reliability-dependent imperfect production. we investigate this model under the uncertain environment of fuzzy numbers with the rate of change of stock level expressed by granular Caputo fractional fuzzy derivative of order . The demands depend on the selling price, product quality, and stock level of the product displayed in the store. The unit production cost depends on development cost due to reliability, raw material cost, and wear tear cost. Here state, co-state variables and parameters are taken as uncertain variables with triangular fuzzy numbers and using granular dierentiability the existence and uniqueness of solution to the fractional dierential system with fuzzy variables and parameters. The production inventory optimal control problem for the fractional system is proposed and a necessary condition for optimality is obtained. Finally, this optimal control problem was solved by using the Pontryagin Maximum principle and for numerical results and graphical representation.
期刊介绍:
Fuzzy Information and Engineering—An International Journal wants to provide a unified communication platform for researchers in a wide area of topics from pure and applied mathematics, computer science, engineering, and other related fields. While also accepting fundamental work, the journal focuses on applications. Research papers, short communications, and reviews are welcome. Technical topics within the scope include: (1) Fuzzy Information a. Fuzzy information theory and information systems b. Fuzzy clustering and classification c. Fuzzy information processing d. Hardware and software co-design e. Fuzzy computer f. Fuzzy database and data mining g. Fuzzy image processing and pattern recognition h. Fuzzy information granulation i. Knowledge acquisition and representation in fuzzy information (2) Fuzzy Sets and Systems a. Fuzzy sets b. Fuzzy analysis c. Fuzzy topology and fuzzy mapping d. Fuzzy equation e. Fuzzy programming and optimal f. Fuzzy probability and statistic g. Fuzzy logic and algebra h. General systems i. Fuzzy socioeconomic system j. Fuzzy decision support system k. Fuzzy expert system (3) Soft Computing a. Soft computing theory and foundation b. Nerve cell algorithms c. Genetic algorithms d. Fuzzy approximation algorithms e. Computing with words and Quantum computation (4) Fuzzy Engineering a. Fuzzy control b. Fuzzy system engineering c. Fuzzy knowledge engineering d. Fuzzy management engineering e. Fuzzy design f. Fuzzy industrial engineering g. Fuzzy system modeling (5) Fuzzy Operations Research [...] (6) Artificial Intelligence [...] (7) Others [...]