OVERVIEW

Operations Research is a discipline included in the class of decision science and management science. The teaching unit introduces the fundamental concepts of the subject, with particular attention to applications in freight and passenger transport sector.

AIMS AND CONTENT

LEARNING OUTCOMES

The aim of the course is to give students the basics of operations research, which are most relevant to the strategic and operational planning of enterprises. Emphasis will be given to the field of logistics and transport. The course is aimed at developing optimization models for decision making problems. Skilled in problem solving with spreadsheet optimization are provided

AIMS AND LEARNING OUTCOMES

Main objectives of the teaching unit are:

- To provide students with the basics of Operations Research most relevant to the strategic and operational planning of companies, with particular reference to the logistics and transport sector.

- To provide the skills to develop, solve and analyse optimisation models for solving relevant decision-making problems in the freight and passenger transport sector.

Expected learning outcomes (Dublin descriptors):

1. Knowledge and understanding: The student will be able to describe the main models and methods of linear and network optimisation in the context of production, logistics and transport planning.

2. Applying knowledge and understanding: The student will be able to apply mathematical optimisation models to real-world problems in production, services and transport, using specific software (e.g. Excel) for solving and analysing results.

3. Making judgements: The student will be able to autonomously evaluate the choice of the most appropriate model and solution method according to the proposed problem and available resources.

4. Communication skills: The student will be able to present and discuss optimisation problem solutions using appropriate terminology and IT tools, both in written and oral form.

5. Learning skills: The student will be able to independently deepen the topics covered and update their skills in the field of operations research. 

PREREQUISITES

No specific prerequisites are required. Basic knowledge of mathematics and economics is assumed.

TEACHING METHODS

Traditional lectures with the use of PCs in the classroom for slide projection, use of software environments and web resources. If in-person activities are not possible, the teaching methods decided by the Degree Programme Board will be adopted (mixed mode: in-person and online, synchronous and/or asynchronous). Please refer to the Aulaweb course page for updates. 

Students with certification of disability, specific learning disorders (DSA), or special educational needs should contact, at the beginning of the course, both the instructor and the Department’s disability liaison, Prof.ssa Elena Lagomarsino (elena.lagomarsino@unige.it) to agree on teaching and examination arrangements that, while respecting the objectives of the teaching unit, take into account individual learning needs and allow the use of compensatory tools if necessary.

SYLLABUS/CONTENT

Consistently with the aims of the teaching unit described above, the contents are as follows:

- Introduction to Operations Research. Introduction to decision problems and optimisation models. 

- Linear Programming (LP) problems. Prototypical problems: production planning (single and multi-period), transportation problems (single and multi-level).

- Graphical method for solving LP problems. Definition of the feasible region. Geometric properties of LP.

- The Simplex algorithm. Solving LP problems of maximum profit and minimum cost.

- Use of Excel for the formulation and solution of LP problems.

- Solution analysis. Identification of scarce resources.

- Introduction to inventory management. Definition of optimal stock level. ABC classification. Solution and formulation of case studies with Excel. Demand forecasting analysis.

- Network optimisation problems. Graphs: basic definitions.

- Shortest path problem and its generalisations.

- Definition of minimum cost infrastructures (spanning tree).

- Network flow problems. Maximum flow problems. Identification of bottlenecks in a network. Minimum cost flow problems.

- Binary optimisation problems. Capital budgeting problem. Assignment problem.

- Discrete optimisation problems. Integer variable constraints.

- Solution methods for discrete optimisation problems: enumerative methods (Branch & Bound).

RECOMMENDED READING/BIBLIOGRAPHY

• Adopted textbook: Introduction to Operations Research: 2024 Release ISE, by Frederick S. Hillier, Gerald J. Lieberman, Mc Graw 

• Handouts and notes provided by the instructor on Aulaweb during the lessons

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

Sem: I

Starting from September 2026

Class schedule

OPERATIONS RESEARCH

EXAMS

EXAM DESCRIPTION

Student learning is assessed through a written examination comprising both practical exercises and critical analysis on proposed problem solutions.

The final written examination may be preceded by one or more mid-term tests.

Online registration is mandatory for all examination sessions.

ASSESSMENT METHODS

Learning assessment is based on a written examination comprising both practical exercises and critical analysis and discussion of proposed problem solutions.

During the course, students will be asked to complete in-class exercises designed to assess their understanding of the topics covered. These exercises may be evaluated and may contribute to the final grade according to arrangements specified by the instructor.

Students may sit the examination in any of the scheduled examination sessions. There are no restrictions on the number of examination attempts in the event of an unsuccessful outcome.

FURTHER INFORMATION