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 the transport of goods and people.

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 certified disabilities, specific learning disorders (DSA) or special educational needs should contact, at the beginning of the lessons, both the instructor and the Department's disability liaison, Prof. Serena Scotto (scotto@economia.unige.it), to agree on teaching and examination methods that, while respecting the objectives of the teaching unit, take into account individual learning methods and allow the use of any compensatory tools.

SYLLABUS/CONTENT

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

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

- 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). In all topics, case studies in the various sectors of freight and passenger transport will be developed and analysed, with individual and group exercises in class (which will be an integral part of the final assessment). 

RECOMMENDED READING/BIBLIOGRAPHY

• Adopted textbook: F.S. Hillier, G.J. Lieberman, “Introduction to Operations Research”, 9th Edition, McGraw-Hill, New York, 2016, chapters 1-7 (selected parts indicated during the course).
• Handouts and notes provided by the instructor on Aulaweb during the lessons.
• F.S. Hillier, G.J. Lieberman, “Ricerca Operativa. Fondamenti”, McGraw-Hill, Milano, 2010 (Italian edition).

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

Sem: I

Starting from September 15 2025

Class schedule

OPERATIONS RESEARCH

EXAMS

EXAM DESCRIPTION

Learning is assessed through a written exam including exercises and critical analysis of proposed problem solutions. 

During the course, exercises are proposed to attending students to verify learning on the topics just covered; these exercises, completed within a set time, contribute additional points to the final written exam score.

Online registration is required to take the exam.

The exam can be taken at any session; there are no limits to the number of attempts in case of failure. 

ASSESSMENT METHODS

During the course, exercises and case studies will be proposed, possibly to be analysed in groups, in order to verify the effectiveness of learning. Successful exercises will contribute to a (supplementary) assessment in addition to the examination.

FURTHER INFORMATION