Strategy Optimization of Supply Chain Enterprises Based on Fuzzy Decision Making Model in Internet of Things

Yue, Xiaoyun; Chen, Yehua

doi:10.1109/access.2018.2879813

Cited by 15 publications

(5 citation statements)

References 13 publications

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“…Different supply chains have witnessed significant changes over the past decades, which can be attributed to several factors, including a high degree of flexibility, low-volume, low-cost production, and short delivery times [1]- [5]. Moreover, a diverse and dynamic nature of market demand has driven some of the innovative methods used by manufacturers to satisfy customer demands on time.…”

Section: Introductionmentioning

confidence: 99%

An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”

Pasha

Dulebenets

Kavoosi³

et al. 2020

IEEE Access

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The "factory-in-a-box" concept involves assembling production modules (i.e., factories) in containers and transporting the containers to different customer locations. Such a concept could be highly effective during emergencies, when there is an urgent demand for products (e.g., the COVID-19 pandemic). The "factory-in-a-box" planning problem can be divided into two sub-problems. The first sub-problem deals with the assignment of raw materials to suppliers, sub-assembly decomposition, assignment of subassembly modules to manufacturers, and assignment of tasks to manufacturers. The second sub-problem focuses on the transport of sub-assembly modules between suppliers and manufacturers by assigning vehicles to locations, deciding the order of visits for suppliers, manufacturers, and customers, and selecting the appropriate routes within the transportation network. This study addresses the second sub-problem, which resembles the vehicle routing problem, by developing an optimization model and solution algorithms in order to optimize the "factory-in-a-box" supply chain. A mixed-integer linear programming model, which aims to minimize the total cost of the "factory-in-a-box" supply chain, is presented in this study. CPLEX is used to solve the model to the global optimality, while four metaheuristic algorithms, including the Evolutionary Algorithm, Variable Neighborhood Search, Tabu Search, and Simulated Annealing, are employed to solve the model for large-scale problem instances. A set of numerical experiments, conducted for a case study of "factory-in-a-box", demonstrate that the Evolutionary Algorithm outperforms the other metaheuristic algorithms developed for the model. Some managerial insights are outlined in the numerical experiments as well. INDEX TERMS Factory-in-a-box, metaheuristics, supply chains, urgent demand, vehicle routing problem.

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Section: Introductionmentioning

confidence: 99%

An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”

Pasha

Dulebenets

Kavoosi³

et al. 2020

IEEE Access

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“…erefore, in some heavy disciplines and engineering calculations, intelligent robots have advantages over humans. Related scholars believe that there are differences in human intelligence [18]. e theory of multiple intelligences points out that each person possesses nine relatively independent intelligences, and these intelligences are presented in a combined form in each individual.…”

Section: Related Workmentioning

confidence: 99%

Construction and Application of College English Multiple Intelligence Teaching Model Based on Internet of Things

Zhou

2022

Mathematical Problems in Engineering

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An RFID sensor is installed above the classroom door, and the scanning distance is set to 8 m to identify the composite campus cards of incoming and outgoing teachers and students, so as to realize automatic statistics of teachers’ theoretical teaching workload and automatic attendance of students’ theoretical class hours. The system automatically starts the multimedia equipment just 5 minutes before class and conducts self-checks on all devices in advance, reducing teachers’ preclass operation steps. The multimedia management system of all classrooms is connected to the campus network and is centrally controlled by the cloud system. When the multimedia equipment in a classroom fails, it can directly instruct teachers to change to an idle classroom. Using the relevant theories of educational psychology and teaching theory, the WPBL teaching model based on the theory of multiple intelligences is expounded and demonstrated. It focuses on expounding theories and ideas; relationships and structures; and environment and resources and conducts in-depth discussions on relevant design rationales and architectural levels. Research has found that students are more interested in reading English than before. The reason is that in the English reading class of the experimental class, basically every student can have their own teaching activities, and more students like to participate in these activities. Applying the theory of multiple intelligences to English reading teaching has played a positive role in stimulating students’ interest in reading. Multiple intelligence English reading activities play an important role in improving students’ English reading performance. Through various teaching activities, the students in the experimental class are more interested and confident in the English reading class. Applying the theory of multiple intelligences to the English reading class can improve the students’ English reading performance and reading ability. In order to apply the theory of multiple intelligences to actual English reading teaching, when designing personalized English reading activities, teachers should learn to combine the theory with the purpose and content of English reading teaching.

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“…Bidang Manufaktur dan Industri menerapkan IoT untuk kontrol peralatan dan suplai logistik [13]. Sektor industri dan manufaktur memanfaatkan IoT untuk pengambilan keputusan pada rantai produksi [23]. Industri dan manufaktor melakukan integrasi IoT untuk pada sistem control produksi untuk memudahkan pengambilan keputusan terkait produksi dan tenaga kerja.…”

Section: Nounclassified

“…Fuzzy Decision Making merupakan model yang pioneer dalam pengambilan keputusan dengan variasi data yang besar. Teori fuzzy mengedepankan ketidakpastian dan ketidakjelasan variabelvariabel informasi [23]. Metode fuzzy sangat cocok diterapkan pada optimalisasi pengambilan keputusan dengan varibel berpengaruh yang cukup besar.…”

Section: No Model Decision Makingunclassified

Decision Making in Internet of Things (IoT) : A Systematic Literature Review

Yomeldi

2020

ITEJ

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Today’s internet technologies support everything that human do. By using integrated technologies the things that connected to internet can provide data. The Internet of Things (IoT) is the new paradigm in provide the data without human communicated. The IoT system support machine to machine communication that can be used to develop smart services that can generate a lot of data. This exponential data can support a decision making. The decision making system depend on availability and reliability of data. This study focus to how the Internet of Thing support decision making system. With a survey of literature to understand the trends, models and factors of decision making in IoT based on previous research. This survey following step by conduct the research question (RQ), then search and observation the previous research from database journal. Based on reviewing 26 articles, this study conclude that the trends of decision making in IoT are implemented on Manufacturing and Industry, Healthcare, Agriculture and Transportation. Besides that the decision model that can support by IoT used Fog Computing, Fuzzy, Game Theoritic, Clustering Based on Multimodal Data Correlation, etc. Meanwhile the decision making factors that influenced by IoT like Latency, data-driven, security, data reliability and accurate. The integrated of model and point of interest on decision making in IoT should be improved. It will be the opportunities and challenge in IoT to support decision making in future.

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Strategy Optimization of Supply Chain Enterprises Based on Fuzzy Decision Making Model in Internet of Things

Cited by 15 publications

References 13 publications

An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”

An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”

Construction and Application of College English Multiple Intelligence Teaching Model Based on Internet of Things

Decision Making in Internet of Things (IoT) : A Systematic Literature Review

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