Searching for queueing : 23 results found | RSS Feed for this search

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15.072J Queues: Theory and Applications (MIT) 15.072J Queues: Theory and Applications (MIT)

Description

This class deals with the modeling and analysis of queueing systems, with applications in communications, manufacturing, computers, call centers, service industries and transportation. Topics include birth-death processes and simple Markovian queues, networks of queues and product form networks, single and multi-server queues, multi-class queueing networks, fluid models, adversarial queueing networks, heavy-traffic theory and diffusion approximations. The course will cover state of the art results which lead to research opportunities. This class deals with the modeling and analysis of queueing systems, with applications in communications, manufacturing, computers, call centers, service industries and transportation. Topics include birth-death processes and simple Markovian queues, networks of queues and product form networks, single and multi-server queues, multi-class queueing networks, fluid models, adversarial queueing networks, heavy-traffic theory and diffusion approximations. The course will cover state of the art results which lead to research opportunities.

Subjects

modeling | modeling | queueing | queueing | queues | queues | queueing systems | queueing systems | communications | communications | manufacturing | manufacturing | computers | computers | call centers | call centers | service industries | service industries | transportation | transportation | applications | applications | birth-death processes | birth-death processes | markovian queues | markovian queues | networks | networks | single-server | single-server | multi-server | multi-server | multi-class queueing | multi-class queueing | fluid models | fluid models | adversarial queueing | adversarial queueing | heavy-traffic theory | heavy-traffic theory | diffusion approximations | diffusion approximations

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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1.203J Logistical and Transportation Planning Methods (MIT) 1.203J Logistical and Transportation Planning Methods (MIT)

Description

The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics. The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics.

Subjects

1.203 | 1.203 | 6.281 | 6.281 | 15.073 | 15.073 | 16.76 | 16.76 | ESD.216 | ESD.216 | logistics | logistics | transportation | transportation | hypercube models | hypercube models | barrier example | barrier example | operations research | operations research | spatial queues | spatial queues | queueing models | queueing models | network models | network models | TSP | TSP | heuristics | heuristics | geometrical probabilities | geometrical probabilities | Markov | Markov | quantitative techniques | quantitative techniques | transportation systems analysis | transportation systems analysis | urban service systems | urban service systems | emergency services | emergency services | random variables | random variables | multi-server queueing theory | multi-server queueing theory | spatial location theory | spatial location theory | network analysis | network analysis | graph theory | graph theory | simulation | simulation | urban OR | urban OR

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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15.072J Queues: Theory and Applications (MIT)

Description

This class deals with the modeling and analysis of queueing systems, with applications in communications, manufacturing, computers, call centers, service industries and transportation. Topics include birth-death processes and simple Markovian queues, networks of queues and product form networks, single and multi-server queues, multi-class queueing networks, fluid models, adversarial queueing networks, heavy-traffic theory and diffusion approximations. The course will cover state of the art results which lead to research opportunities.

Subjects

modeling | queueing | queues | queueing systems | communications | manufacturing | computers | call centers | service industries | transportation | applications | birth-death processes | markovian queues | networks | single-server | multi-server | multi-class queueing | fluid models | adversarial queueing | heavy-traffic theory | diffusion approximations

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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2.854 Manufacturing Systems I (SMA 6304) (MIT) 2.854 Manufacturing Systems I (SMA 6304) (MIT)

Description

As the first in a sequence of four half-term courses, this course will provide the fundamental building blocks for conceptualizing, understanding and optimizing manufacturing systems and supply chains. These building blocks include process analysis, queuing theory, simulation, forecasting, inventory theory and linear programming. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6304 (Manufacturing Systems I: Analytical Methods and Flow Models). As the first in a sequence of four half-term courses, this course will provide the fundamental building blocks for conceptualizing, understanding and optimizing manufacturing systems and supply chains. These building blocks include process analysis, queuing theory, simulation, forecasting, inventory theory and linear programming. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6304 (Manufacturing Systems I: Analytical Methods and Flow Models).

Subjects

conceptualizing | conceptualizing | understanding and optimizing manufacturing systems and supply chains | understanding and optimizing manufacturing systems and supply chains | process analysis | process analysis | queueing theory | queueing theory | simulation | simulation | forecasting | forecasting | inventory theory | inventory theory | linear programming | linear programming | conceptualizing | understanding and optimizing manufacturing systems and supply chains | conceptualizing | understanding and optimizing manufacturing systems and supply chains | SMA 6304 | SMA 6304

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.263J Data Communication Networks (MIT) 6.263J Data Communication Networks (MIT)

Description

6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control. 6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control.

Subjects

data communication networks | data communication networks | architecture | architecture | network performance | network performance | network operation | network operation | next generation data networks | next generation data networks | network algorithms | network algorithms | mathematics | mathematics | probability theory | probability theory | layered network architecture | layered network architecture | Link Layer protocols | Link Layer protocols | high-speed packet switching | high-speed packet switching | queueing theory | queueing theory | Local Area Networks | Local Area Networks | Wide Area Networks | Wide Area Networks | 6.263 | 6.263 | 16.37 | 16.37

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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1.203J Logistical and Transportation Planning Methods (MIT)

Description

The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics.

Subjects

1.203 | 6.281 | 15.073 | 16.76 | ESD.216 | logistics | transportation | hypercube models | barrier example | operations research | spatial queues | queueing models | network models | TSP | heuristics | geometrical probabilities | Markov | quantitative techniques | transportation systems analysis | urban service systems | emergency services | random variables | multi-server queueing theory | spatial location theory | network analysis | graph theory | simulation | urban OR

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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1.203J Logistical and Transportation Planning Methods (MIT)

Description

The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics.

Subjects

1.203 | 6.281 | 15.073 | 16.76 | ESD.216 | logistics | transportation | hypercube models | barrier example | operations research | spatial queues | queueing models | network models | TSP | heuristics | geometrical probabilities | Markov | quantitative techniques | transportation systems analysis | urban service systems | emergency services | random variables | multi-server queueing theory | spatial location theory | network analysis | graph theory | simulation | urban OR

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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15.761 Operations Management (MIT) 15.761 Operations Management (MIT)

Description

This course will introduce concepts and techniques for design, planning and control of manufacturing and service operations. The course provides basic definitions of operations management terms, tools and techniques for analyzing operations, and strategic context for making operational decisions. We present the material in five modules: Operations Analysis Coordination and Planning Quality Management Project Management Logistics and Supply Chain Management This course will introduce concepts and techniques for design, planning and control of manufacturing and service operations. The course provides basic definitions of operations management terms, tools and techniques for analyzing operations, and strategic context for making operational decisions. We present the material in five modules: Operations Analysis Coordination and Planning Quality Management Project Management Logistics and Supply Chain Management

Subjects

manufacturing | manufacturing | service | service | analyzing operations | analyzing operations | operational decisions | operational decisions | operations analysis | operations analysis | quality management | quality management | project management | project management | logistics | logistics | supply chain management | supply chain management | job shop operations | job shop operations | process matching | process matching | queuing | queuing | forecasting | forecasting | queueing | queueing | analysis | analysis | analyzing | analyzing | operations | operations | coordination | coordination | planning | planning | quality | quality | project | project | management | management | supply chain | supply chain | job shop | job shop | decisions | decisions | decision making | decision making | operational | operational | design | design | control | control | materials | materials | production | production | scheduling | scheduling | reengineering | reengineering | capacity | capacity | facilities | facilities | strategy | strategy | process | process | processes | processes | matching | matching | inventory | inventory | vendor | vendor | customer | customer

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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15.070J Advanced Stochastic Processes (MIT) 15.070J Advanced Stochastic Processes (MIT)

Description

This class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models. This class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.

Subjects

analysis | analysis | modeling | modeling | stochastic processes | stochastic processes | theoretic probability | theoretic probability | martingales | martingales | filtration | filtration | stopping theorems | stopping theorems | large deviations theory | large deviations theory | Brownian motion | Brownian motion | reflected Brownian motion | reflected Brownian motion | stochastic integration | stochastic integration | Ito calculus | Ito calculus | functional limit theorems | functional limit theorems | applications | applications | finance theory | finance theory | insurance | insurance | queueing | queueing | inventory models | inventory models

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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15.070 Advanced Stochastic Processes (MIT) 15.070 Advanced Stochastic Processes (MIT)

Description

The class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models. The class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.

Subjects

analysis | analysis | modeling | modeling | stochastic processes | stochastic processes | theoretic probability | theoretic probability | martingales | martingales | filtration | filtration | stopping theorems | stopping theorems | large deviations theory | large deviations theory | Brownian motion | Brownian motion | reflected Brownian motion | reflected Brownian motion | stochastic integration | stochastic integration | Ito calculus | Ito calculus | functional limit theorems | functional limit theorems | applications | applications | finance theory | finance theory | insurance | insurance | queueing | queueing | inventory models | inventory models

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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1.203J Logistical and Transportation Planning Methods (MIT) 1.203J Logistical and Transportation Planning Methods (MIT)

Description

The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics. The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics.

Subjects

logistics | logistics | transportation | transportation | hypercube models | hypercube models | barrier example | barrier example | operations research | operations research | spatial queues | spatial queues | queueing models | queueing models | network models | network models | TSP | TSP | heuristics | heuristics | geometrical probablities | geometrical probablities | Markov | Markov | 1.203 | 1.203 | 6.281 | 6.281 | 15.073 | 15.073 | 16.76 | 16.76 | ESD.216 | ESD.216

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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1.203J Logistical and Transportation Planning Methods (MIT)

Description

The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics.

Subjects

1.203 | 6.281 | 15.073 | 16.76 | ESD.216 | logistics | transportation | hypercube models | barrier example | operations research | spatial queues | queueing models | network models | TSP | heuristics | geometrical probabilities | Markov | quantitative techniques | transportation systems analysis | urban service systems | emergency services | random variables | multi-server queueing theory | spatial location theory | network analysis | graph theory | simulation | urban OR

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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1.203J Logistical and Transportation Planning Methods (MIT)

Description

The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics.

Subjects

logistics | transportation | hypercube models | barrier example | operations research | spatial queues | queueing models | network models | TSP | heuristics | geometrical probablities | Markov | 1.203 | 6.281 | 15.073 | 16.76 | ESD.216

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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15.070 Advanced Stochastic Processes (MIT)

Description

The class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.

Subjects

analysis | modeling | stochastic processes | theoretic probability | martingales | filtration | stopping theorems | large deviations theory | Brownian motion | reflected Brownian motion | stochastic integration | Ito calculus | functional limit theorems | applications | finance theory | insurance | queueing | inventory models

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.263J Data Communication Networks (MIT)

Description

6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control.

Subjects

data communication networks | architecture | network performance | network operation | next generation data networks | network algorithms | mathematics | probability theory | layered network architecture | Link Layer protocols | high-speed packet switching | queueing theory | Local Area Networks | Wide Area Networks | 6.263 | 16.37

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.263J Data Communication Networks (MIT)

Description

6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control.

Subjects

data communication networks | architecture | network performance | network operation | next generation data networks | network algorithms | mathematics | probability theory | layered network architecture | Link Layer protocols | high-speed packet switching | queueing theory | Local Area Networks | Wide Area Networks | 6.263 | 16.37

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.263J Data Communication Networks (MIT)

Description

6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control.

Subjects

data communication networks | architecture | network performance | network operation | next generation data networks | network algorithms | mathematics | probability theory | layered network architecture | Link Layer protocols | high-speed packet switching | queueing theory | Local Area Networks | Wide Area Networks | 6.263 | 16.37

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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1.203J Logistical and Transportation Planning Methods (MIT)

Description

The class will cover quantitative techniques of Operations Research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, pick-up and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, emergency repair services). It presents a unified study of functions of random variables, geometrical probability, multi-server queueing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. There will be discussion focused on the difficulty of implementation, among other topics.

Subjects

logistics | transportation | hypercube models | barrier example | operations research | spatial queues | queueing models | network models | TSP | heuristics | geometrical probablities | Markov | 1.203 | 6.281 | 15.073 | 16.76 | ESD.216

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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15.070 Advanced Stochastic Processes (MIT)

Description

The class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.

Subjects

analysis | modeling | stochastic processes | theoretic probability | martingales | filtration | stopping theorems | large deviations theory | Brownian motion | reflected Brownian motion | stochastic integration | Ito calculus | functional limit theorems | applications | finance theory | insurance | queueing | inventory models

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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15.761 Operations Management (MIT)

Description

This course will introduce concepts and techniques for design, planning and control of manufacturing and service operations. The course provides basic definitions of operations management terms, tools and techniques for analyzing operations, and strategic context for making operational decisions. We present the material in five modules: Operations Analysis Coordination and Planning Quality Management Project Management Logistics and Supply Chain Management

Subjects

manufacturing | service | analyzing operations | operational decisions | operations analysis | quality management | project management | logistics | supply chain management | job shop operations | process matching | queuing | forecasting | queueing | analysis | analyzing | operations | coordination | planning | quality | project | management | supply chain | job shop | decisions | decision making | operational | design | control | materials | production | scheduling | reengineering | capacity | facilities | strategy | process | processes | matching | inventory | vendor | customer

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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2.854 Manufacturing Systems I (SMA 6304) (MIT)

Description

As the first in a sequence of four half-term courses, this course will provide the fundamental building blocks for conceptualizing, understanding and optimizing manufacturing systems and supply chains. These building blocks include process analysis, queuing theory, simulation, forecasting, inventory theory and linear programming. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6304 (Manufacturing Systems I: Analytical Methods and Flow Models).

Subjects

conceptualizing | understanding and optimizing manufacturing systems and supply chains | process analysis | queueing theory | simulation | forecasting | inventory theory | linear programming | conceptualizing | understanding and optimizing manufacturing systems and supply chains | SMA 6304

License

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15.070J Advanced Stochastic Processes (MIT)

Description

This class covers the analysis and modeling of stochastic processes. Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.

Subjects

analysis | modeling | stochastic processes | theoretic probability | martingales | filtration | stopping theorems | large deviations theory | Brownian motion | reflected Brownian motion | stochastic integration | Ito calculus | functional limit theorems | applications | finance theory | insurance | queueing | inventory models

License

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6.263J Data Communication Networks (MIT)

Description

6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control.

Subjects

data communication networks | architecture | network performance | network operation | next generation data networks | network algorithms | mathematics | probability theory | layered network architecture | Link Layer protocols | high-speed packet switching | queueing theory | Local Area Networks | Wide Area Networks | 6.263 | 16.37

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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