OPTIMIZATION METHODS

iten
Code
101122
ACADEMIC YEAR
2020/2021
CREDITS
6 credits during the 1st year of 10948 MARITIME SCIENCE AND TECHNOLOGY (L-28) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR
MAT/09
LANGUAGE
English
TEACHING LOCATION
GENOVA (MARITIME SCIENCE AND TECHNOLOGY)
semester
2° Semester
Teaching materials

OVERVIEW

The aim of the course is to provide students with basic knowledge on mathematical optimization models and methods to solve decision problems useful for the training of maritime personnel and, in particular, for the profession of engineer and deck officers.

AIMS AND CONTENT

LEARNING OUTCOMES

The Course introduces to optimization models and methods for the solution of decision problems, with particular attention to models and problems arising in Maritime. In particular the focus will be on route planning, cargo loading and stowage, flow management.

AIMS AND LEARNING OUTCOMES

The course aims at presenting the subject in its theoretical, methodological and applicative aspects in order to provide students with knowledge of the applicable models and methodologies to be used to solve different types of problems. The laboratory aims at providing the student with the knowledge and skills to use specific software to solve the practical problems faced.

The practical problems addressed in the course concern problems of interest for the profession of engineer and deck officers such as: stowage and loading of different types of ships, route planning, crew scheduling, flow of people in emergency situations, search and rescue techniques, inventory and warehouse management.

With reference to learning outcomes, at the end of the course the students must have acquired competences that allow them to understand, describe and solve different types of real problems in maritime trasports, develop models and methods and use optimization software environments with a certain mastery of reference. Specifically, at the end of the course, the students will:

  • Know and understand the main optimization tools and methods that allow them to identify the best decision to be taken in different application contexts in maritime field.
  • Know the main elements of a decision problem in terms of decision makers involved, type of data available, variables, constraints and objectives.
  • Apply the acquired knowledge to describe, formalize and solve real problems, even different from those proposed during the lessons, using the correct models and optimization methods learned.
  • Use both the conceptual and operational knowledge acquired with independent assessment and critical reasoning skills, developing original models applicable in the working context in which they will operate.
  • Having acquired a correct terminology and technical language to clearly communicate the main elements of the decision-making process and of the optimization method used.
  • Developed learning skills that will enable them to study and apply the main topics of the discipline in the context in which they will work.

PREREQUISITES

Mathematics and Algebra

TEACHING METHODS

Lectures, computer labs using application software, small group activities on case studies and project development.

In the case of still lacking health emergency situation, the updated distance and/or blended teaching methods will be communicated on the Aulaweb website of the course (registration required and recommended).

 

SYLLABUS/CONTENT

In each part of the course the theoretical part, aimed at providing the basic methodological contents, will be flanked by the practical laboratory, carried out in the computer lab, through the use of appropriate software environments (excel, lindo) used to formalize and solve the practical problems addressed.

Part I:

  • Introduction to Operations Research and problem solving: from real problems to mathematical models.
  • Classification of models and optimization methods. Unconstrained and constrained optimization, linear, non-linear and integer programming.
  • Introduction to linear programming (LP).
  • The transportation problem.
  • Using Excel and Lindo for formulating and solving LP optimization problems.

 

Part II:

  • Network optimization problems.
  • Graphs: properties, definitions and basic terminology of network
  • Shortest path problem and optimal path models
  • Maximum flow and minimum cost flow problem
  • Network models and techniques for project management
  • Using Excel and Lindo for formulating and solving network optimization problems
  • Route planning, search and rescue techniques, flow of people and management of emergency plans

 

Part III:

  • Integer programming (IP) and binary programming (BIP).
  • Use of binary variables and logical constraints.
  • Set covering, set partitioning and set packing problems
  • Using Excel and Lindo for formulating and solving IP an BIP problems
  • Ship Stowage and loading; crew scheduling.

 

Part IV:

  • Forecasting methods, regression models and moving average techniques.
  • Inventory theory and warehouse management. The economic lot size model.
  • Using Excel for forecasting and for solving inventory models.

RECOMMENDED READING/BIBLIOGRAPHY

The text books and any supplementary materials will be communicated at the beginning of the lessons and published in Aulaweb

TEACHERS AND EXAM BOARD

Office hours: Wednesday h.13.30-14.30 - Department of Economics - I floor Remote reception on request: contact the teacher via email (etanfani@economia.unige.it)  

Exam Board

ELENA TANFANI (President)

DANIELA AMBROSINO (President Substitute)

ANNA FRANCA SCIOMACHEN (President Substitute)

LESSONS

TEACHING METHODS

Lectures, computer labs using application software, small group activities on case studies and project development.

In the case of still lacking health emergency situation, the updated distance and/or blended teaching methods will be communicated on the Aulaweb website of the course (registration required and recommended).

 

LESSONS START

5th March 2021

Class schedule

All class schedules are posted on the EasyAcademy portal.

EXAMS

EXAM DESCRIPTION

The achievement verification of the expected learning outcomes is evaluated with a written test and with a project work (in small groups) and/or a practical test in the computer lab.

 

ASSESSMENT METHODS

The written test is aimed at assessing the degree of knowledge of the theoretical topics discussed in class. While the capacity of critical evaluation and reasoning and the ability to apply the acquired knowledge is assessed through the project work and/or the practical test.

Exam schedule

Date Time Location Type Notes
20/01/2021 09:00 GENOVA Scritto
03/02/2021 09:00 GENOVA Scritto
18/02/2021 09:00 GENOVA Scritto
10/06/2021 09:00 GENOVA Scritto
24/06/2021 09:00 GENOVA Scritto
14/07/2021 09:00 GENOVA Scritto
02/09/2021 09:00 GENOVA Scritto

FURTHER INFORMATION

The course is available on Aulaweb