The course aims to provide knowledge of some math programming techniques to solve strategic, tactical and operational problems arising in supply chain management. The definition of evaluation criteria for possible solutions, the development of mathematical models and heuristic methods for determining the optimal solution, optimum Pareto solutions are the focus of the course.
The course aims at providing tools to face strategic, tactical and operational decisions in the Supply Chain Management; it will provide management techniques (math programming, scenario analysis). The consolidation of the proposed methodologies is supported by the development of case studies; models will be implemented and solved thanks to optimization software and spreadsheet Excel.
The course aims at providing tools to face strategic, tactical and operational decisions in the Supply Chain Management.
The course will provide management techniques such as decision theory, math programming, scenario analysis. The consolidation of the proposed methodologies is supported by the development of case studies; models will be implemented and solved thanks to optimization software and spreadsheet Excel.
At the end of the course students will be able to:
• analyse a decision problem and understand the best way to face it
• apply different criteria to evaluate the alternatives by using to Payoff Table
• formulate a decision problem and implement a mathematical linear programming model (integer-binary)
• solve some of the typical problems in the supply chain management
• critically analyse the solutions obtained by assessing their correctness and feasibility
• carry out scenario analyses and compare the alternatives
Matrices and linear systems
Functions of a real variable
Traditional lectures in Italian are integrated with lab lessons, seminars and individual/group works.
Please note that, if required by the health and epidemiological situation, lessons will be on line via the Teams platform. Updated information will be available on Aulaweb.
9 ECTS credits
Analysis of some problems in the supply chain management: production, scheduling, transportation and distribution problems; network design problems; inventory management and forecasting. Project management: analysis of costs and times.
Methods: Decision theory, Linear, Integer and binary programming, multi-objective optimization, graph theory, what if analysis, CPM tecniques. Some software will be used for solving the analysed problems (i.e. LINDO, MPL, Excel)
6 ECTS credits
Analysis of some problems in the supply chain management: production, scheduling, transportation and distribution problems; network design problems.Project management: analysis of costs and times.
Methods: Decision theory, Linear, Integer and binary programming, graph theory, what if analysis, heuristics. Some software will be used for solving the analysed problems (i.e. LINDO, MPL, Excel)
Hillier, Lieberman, Introduction to Operations Research, McGraw-Hill 2009. Clement, Robert T., Reilly, Terence. Making hard decisions with decisiontools suite, South Western Pub, 2013. Slides and papers on AULAWEB
Ricevimento: Please, write an email to have an appointment (ambrosin@economia.unige.it)
DANIELA AMBROSINO (President)
ANNA FRANCA SCIOMACHEN
ELENA TANFANI
September 2020
OPERATIONS RESEARCH FOR MANAGEMENT
Written examination and presentation of case studies.
Please note that the written examination will be replaced by an oral one (via the Teams platform) if required by the health and epidemiological situation. Updated information will be available on Aulaweb.
The knowledge on the topics covered in class will be assessed through the written examination
The ability to apply knowledge and communication skills will be assessed through the projects work and thier presentation. The evaluation will concern: 1) the work in the classroom 2) the organization of the work for the information collection 3) compliance with deliveries 4) project presentation (ppt: completeness/ logical sequence of the contents; oral presentation: language appropriateness)
see the webpage
http://www.economia.unige.it/index.php/english/incoming-erasmus-students
OR contact:
ambrosin@economia.unige.it
