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Presentation
Presentation
The Operations Research (OR) course focuses on the application of mathematical and analytical methods to optimize decision-making processes in complex systems. It is essential for civil engineers working in areas such as urban planning, construction, and infrastructure management. This course is relevant to the Civil Engineering curriculum as it provides critical tools for modeling and solving real-world problems involving efficient resource allocation, project management, and risk analysis. The skills acquired in this course are applicable across various engineering domains, such as transportation, construction, and water resource management, contributing to the development of professionals capable of solving problems effectively and sustainably.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor | Semestral | 5
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Year | Nature | Language
Year | Nature | Language
3 | Mandatory | Português
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Code
Code
ULP730-81
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
Introduction to Operations Research History, definition, and application of OR in Civil Engineering. Linear Programming Problem formulation; Simplex Method; Duality; Sensitivity Analysis. Nonlinear Programming Basic concepts; Optimization methods for nonlinear functions. Queueing Theory and Simulation Queueing models; Discrete event simulation; Applications in infrastructure projects. Decision Analysis Decision trees; Risk and uncertainty analysis; Game theory. Optimization in Transportation Networks Network flow; Routing problems; Algorithms for transportation problems. Software Applications in OR Use of computational tools for solving practical problems.
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Objectives
Objectives
The primary learning objectives of this course include developing analytical and mathematical modeling skills applied to process optimization in Civil Engineering. By the end of the course, students should be able to: Understand and apply optimization methods, such as linear and nonlinear programming, to typical engineering problems. Use decision analysis techniques under uncertainty, such as queueing theory and simulation, to solve complex engineering problems. Develop mathematical models for resource optimization, logistics, and transportation networks. Implement algorithms and use specialized Operations Research software to support decision-making processes. Analyze and interpret the results obtained, assessing the feasibility of proposed solutions under different performance criteria.
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Teaching methodologies and assessment
Teaching methodologies and assessment
To promote active and effective learning, the following innovative methodologies will be adopted: Project-Based Learning (PBL): Students will work on real civil engineering problems, applying OR concepts to develop optimized solutions. Computational Simulations: Use of specialized software to model and simulate engineering scenarios, allowing for the visualization and analysis of different solution alternatives. Gamification: Introduction of game elements, such as challenges and competitions, to stimulate student participation and engagement. Case Studies: Analysis of real cases and group discussions to promote critical thinking and practical application of theoretical concepts.
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References
References
Winston, W. L. (2004). Operations Research: Applications and Algorithms. 4th Edition, Cengage Learning. Taha, H. A. (2016). Operations Research: An Introduction. 10th Edition, Pearson Education.
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Office Hours
Office Hours
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Mobility
Mobility
No
