Class Operational Research

The Operations Research course provides second-year undergraduate students with the fundamental concepts and methodologies required to model, analyze, and solve complex decision-making problems. Its scope covers the formulation and application of quantitative optimization techniques, including linear and integer programming, network models, resource allocation, and multi-criteria decision analysis, with applications in engineering, logistics, manufacturing, energy systems, transportation, and service industries. As a core component of the degree programme, the course equips students with analytical thinking, mathematical modelling skills, and computational problem-solving techniques that support evidence-based decision-making. These competencies provide a solid foundation for advanced engineering courses and prepare students to address real-world optimization challenges in their future professional careers.

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Introduction to Operations Research History, definition, and application of OR in Electrical Engineering and Power Systems. Linear Programming Problem formulation; Simplex Method; Duality; Sensitivity Analysis. Introductory Concepts in Nonlinear Programming Basic concepts; Optimization methods for nonlinear functions. Queueing Theory and Simulation Queueing models; Discrete-event simulation; Applications in infrastructure projects. Decision Analysis Introductory concepts in decision trees; Risk and uncertainty analysis; Game theory. Optimization in Transport Networks Network flow; Routing problems; Algorithms specific to transport problems. Software Applications in OR Use of computational tools to solve practical problems

The following approaches will be adopted: To foster active and effective learning, innovative methodologies will be employed, such as: Project-Based Learning (PBL): Students will work on real-world problems in electrical and power systems engineering, applying Operations Research (OR) concepts to develop optimized solutions. Computer Simulations: Use of specialized software to model and simulate engineering scenarios, enabling the visualization and analysis of various solution alternatives. Gamification: Incorporation of game elements-such as challenges and competitions-to encourage student participation and engagement. Case Studies: Analysis of real-world cases and group discussions to promote critical thinking and the practical application of theoretical concepts. Formative Assessment: Continuous assessment and regular feedback will be used to monitor student progress and adjust the teaching approach as needed

Frederick S. Hillier, Gerald J. Lieberman; Introduction to operations research. ISBN: 0-07-118163-6