TecnoCampus Foundation
eCampus
University Business
eCampus

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General information

Subject type: Mandatory

Coordinator: Valeria Bernardo

Trimester: Second term

Credits: 4

Teaching staff: 

Jose Ignacio Monreal Galán

Academic year: 2026

Teaching course: 1

Languages ​​of instruction

  • Spanish

Classes and documentation will be mainly in Spanish.

Competencies / Learning Outcomes

Specific skills

  • Establish maritime and logistics business projects that allow the creation of new companies or the improvement of existing ones, adopting innovative and creative ideas

  • Show knowledge and skills for the coordination of the departments of purchasing, supply, production and distribution of a product to any company, analyzing different types of techniques

  • Operationalize the storage of goods, through computer applications of logistics management

  • Show knowledge of the organization of maritime, land, air and multimodal transport, customs management and international trade in order to manage and / or contract transport

  • Select and use quantitative instruments for decision making and contrasting economic hypotheses

Presentation of the subject

The subject "Quantitative Methods Applied to Logistics" aims to encourage and develop systemic and scientific thinking, allowing students to propose and develop models and solutions to problems of various kinds. 

More specifically, it aims to provide students with a series of tools and methods that allow them to solve real-life problems, and in the logistics field in particular.

 

 The classroom (physical or virtual) is a safe space, free of sexist, racist, homophobic, transphobic and discriminatory attitudes, either towards students or teachers. We trust that together we can create a safe space where we can make mistakes and learn without having to suffer the prejudices of others.

Contents

  1. Introduction
    1. Models: Concepts and typologies
    2. Systems: Concept, principles, and applications
    3. Methods: Concept, importance and utility
    4. Algorithm: Concept, typology and use
  2. Graph theory
    1. Introduction to graphs
      1. Definition, representation and topology
      2. Application examples
      3. Pseudocode: basic concepts, conditional operators and structure.
    2. Road problems
      1. Minimum partial tree
        1. Prim algorithm
        2. Kruskal algorithm
    3. Shorter path
      1. Dijkstra's algorithm
    4. Flow problems
      1. Maximum total flow
      2. Ford-Fulkerson algorithm
    5. Case studies
  3. Linear programming
    1. Introduction to linear programming
      1. What is linear programming?
      2. The first mathematical model
      3. Variable transformations
      4. Transformations of the objective function
      5. Constraints transformations
    2. Graphic resolution
      1. Feasible solutions area
      2. Basic and non-basic variables
      3. Optimal solution
      4. Types of solutions
    3. Dual model and sensitivity analysis
      1. Rules of primal-dual transformation
      2. Meaning of dual variables
      3. Sensitivity analysis of cost coefficients
      4. Sensitivity analysis of independent terms
      5. Dual price utility
    4. Whole and mixed linear programming
      1. Real, integer, and binary variables
      2. Usefulness of binary variables
    5. Case studies: Application to logistics
    6. Using the Excel "Solver" tool
    7. Branch and Bound

Activities and evaluation system

The overall grade of the subject takes into account the following aspects:

  • 40% Face-to-face and pair seminars (Non-refundable)
  • 10% Individual Questionnaires (Non-refundable)
  • 50% Final exam

To pass the subject it is necessary to obtain at least a 4 out of 10 in the final exam.

Recovery:

  • Students who do not appear for the final exam will receive a No Show and will lose the right to the retake exam.
  • Students who fail the subject will be able to take a retake exam that will replace the final exam, therefore, it will correspond to 50% of the final grade and at least a 4 out of 10 is necessary.
  • Seminars and quizzes cannot be recovered.

Given the fundamental nature of this subject, the student is required not only to provide solutions to certain problems, but also to be able to generate them autonomously, without any external help. For this reason, the use of generative artificial intelligences (GAIs) to resolve the problems posed in the subject —whether in seminars, questionnaires or exams— is counterproductive, is strictly prohibited and will be considered a case of plagiarism fraud, where the subject professor may call the student for an individual interview with the aim of verifying authorship. The critical use of GAIs as a vehicle to learn and resolve doubts about the subject is not considered a misuse of these mechanisms, as long as this does not contradict what has been indicated above and the student does not lose sight of the fact that he may obtain incorrect answers and/or not adjusted to the contents of the subject. 

Bibliography

Basic

Hillier FS, Lieberman GJ. Introduction to Operations Research. Editorial McGraw-Hill (9th ed), 2010. ISBN: 0073376299.

Sallán JM, Suñé A, Fernández V, Fonollosa JB. Quantitative methods of industrial organization I. Edicions UPC (2nd ed.), 2005. ISBN: 8483017954.

Vieites Rodíguez, Ana María et al. Graph theory. Exercises and problems solved. Editorial Paraninfo, 2014. ISBN: 9788428337076

Complementary

Taha HA Operations research. Pearson Education Publishing (7th ed.), 2004. ISBN: 9702604982