Teaching plan for the course unit (Short version)
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General information

 

Course unit name: Operational research

Course unit code: 363721

Academic year: 2025-2026

Coordinator: Marcelino Garcia Solera

Department: Department of Econometrics, Statistics and Applied Economics

Credits: 6

Single program: S

Estimated learning time

Total number of hours 150

 

Face-to-face and/or online activities

60

	-  Lecture with practical component	Face-to-face		45
	-  Problem-solving class	Face-to-face		15

Supervised project

40

Independent learning

50

Learning objectives

Referring to knowledge The objectives of the course are to ensure that on its successful completion students are able to: a) process relevant information concerning problems related to business systems, fundamentally, based on the application of linear models, that is, understand the operating conditions of the system in question and make explicit the goals of the business analysis; b) understand and apply appropriate methods and techniques to solve the model formulated; c) interpret the results obtained and, in particular, evaluate the response of the system to changes in the environment and/or in the policy upheld by the decision-making body. Operating in what is primarily a deterministic context, the course also aims to introduce the student to the decision-making process in situations governed by random behaviour.   Referring to abilities, skills Foster the ability to detect and solve decision-making problems using operations research models.   Referring to attitudes, values and norms Highlight the potential utility and limitations of operations research tools as an aid to decision-making in the company.

 

 

Teaching blocks

 

1. Introduction

*  The aim of this block is to provide a general overview of the origins of operations research and of the diversity of business problems that can be addressed taking this approach. Attention is focused initially on deterministic programming models, and the specific meaning of their individual elements (decision variables, constraints, objective function, coefficients, independent terms, etc.) and their use in the context of business management. Students are also introduced to specific stochastic approaches of relevance. By means of a variety of examples, the aim is to highlight the advantages and challenges associated with the process of abstraction involved in the formalization of the object under study. In short, the goal is to illustrate both the potential and limitations of the application of operations research models for providing appropriate solutions to real problems in economics.

2. Deterministic programming models

*  This block specifies the modelling process as applied to linear programming. The solution process is presented intuitively by linking it to students’ prior knowledge of systems of equations. The main objective of this is to facilitate the interpretation of the results obtained, regardless of the procedure used in obtaining them. For this reason, priority is given to efforts linking the analytical solution with the real problem that serves to justify the model employed. In other words, having presented the basic theoretical elements related to algorithms for solving linear programs, attention is now placed on the interpretation of the results and the utility of obtaining valid answers to the questions that in each case have underpinned the initial modelling process.

3. Stochastic models of operations research

*  This block re-examines some of the examples outlined at the beginning of the course that are characterized by the stochastic behaviour of the elements making up the system under study. Statistical processing takes the necessary elements to focus on the use of data to resolve operational issues of economic significance.

 

 

Official assessment of learning outcomes

 

Continuous assessment is the normal mode of evaluation for this course. To pass the course, students must demonstrate sufficient competence, which is confirmed by obtaining at least a passing grade in one of the official exam sittings. To obtain this minimum passing grade, students must sit the corresponding official exam session. The written exam accounts for 50% of the final grade. However, students must obtain a minimum score of 3 out of 10 in the exam, which covers the entire course syllabus. In addition, two in-person practicals are carried out during the course, which together account for 30% of the final grade. Each activity includes a practical case with questions that must be answered individually and in writing, using support materials prepared by the student. A further assessed component, which involves completing tasks outside the classroom—both individually and in groups—accounts for 15% of the final grade. Finally, 5% of the final grade is reserved for evaluating the quality of the student’s participation in class. Repeat assessment of the subject, to be taken on the dates and in accordance with the criteria set by the Academic Board, consists of a final exam with the same format as that of the single mode of assessment.   Examination-based assessment Students have to pass a final exam, which accounts for 100% of the final grade. Students opting for the single mode of assessment must submit a written request to be exempted from the continuous mode, approved by their tutor. The deadline for submitting this request coincides with the day designated for the final exam. Repeat assessment of the subject, to be taken on the dates and in accordance with the criteria set by the Academic Board, consists of test with the same format as that of the final exam.

Reading and study resources

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Book

BAZARAA, Mokntar S.; JARVIS, John J. i SHERALI, Gabuf D. Programación lineal y flujo en redes. México: Limusa. 1999

Catàleg UB  

HILLIER, Frederick S. i LIBERMAN, Gerald J. Introducción a la investigación de operaciones. México: McGraw-Hill. 2010

Catàleg UB  

IJIRI, Yuji. Análisis de objetivos y control de gestión. México: ICE. 1976

Catàleg UB  

RAGSDALE, Cliff T. Spreadsheet Modeling & Decisión Analysis. Mason, Ohio: South-Western, Cengage Learning, 2012

Catàleg UB  

VILLALBA VILA, Daniel. i JEREZ MENDEZ, Miguel. Sistemas de optimización para la planificación y la toma de decisiones. Madrid: Pirámide. 1990

Catàleg UB  

WEINGARTNER, H. Martin. Mathematical Programming and the Analysis of Capital Budgeting Problems. Londres: Kershaw Pub. 1974

Catàleg UB  

WINSTON, Wayne L. Investigación de operaciones : aplicaciones y algoritmos. 4ª ed. México: Thomson, 2005

Catàleg UB  

GARCÍA SOLERA, M., [2024]. Programación lineal : análisis post-óptimo. Barcelona: Universitat de Barcelona Edicions. ISBN 9788491689867.

Catàleg UB