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

Description

This course focuses on quantitative techniques of Operations Research, with an 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). 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. Discussion of implementation difficulties. This course focuses on quantitative techniques of Operations Research, with an 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). 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. Discussion of implementation difficulties.

Subjects

1.203 | 1.203 | 6.281 | 6.281 | 13.665 | 13.665 | 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) 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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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

This course focuses on quantitative techniques of Operations Research, with an 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). 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. Discussion of implementation difficulties.

Subjects

1.203 | 6.281 | 13.665 | 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

Site sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

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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 https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

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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

Site sourced from

http://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

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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

Site sourced from

https://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

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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

Site sourced from

https://ocw.mit.edu/rss/all/mit-allspanishcourses.xml

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