Course Details for A.Y. 2016/2017

The information on this page refer to the academic year 2016/2017. Therefore, several links are not available and data may be incomplete. To read the current information on the course, if it is still available, go to the university course catalogue . To read information relating other academic years, use the list at the bottom of this page.

A. Year:

2016/2017

Name:

Scheduling dei Processi e delle Operazioni / Process and Operations Scheduling

Type:

Module

Main course:

Mathematical modelling and optimization / Mathematical modelling and optimization

Basic information

Code:

Sector:

MAT/09

Credits:

: Bachelor Degree in Computer Science 6 CFU (c)
: Master Degree in Computer Science 6 CFU (c)
: Master Degree in Mathematical Engineering 6 CFU (b)

Term:

1^st semester

Degree(s):

Master Degree in Computer Science 2^nd anno curriculum General Elective
Master Degree in Mathematical Engineering 1^st anno curriculum Comune Compulsory

Language:

English

Teacher(s):

Stefano Smriglio

Same as:

Sistemi Organizzativi

Course Objectives

Train the students in recognizing machine scheduling problems, classify them in terms of computational complexity and solve them by heuristic, approximation or exact algorithms.

Course Content

Elements of a (deterministic) scheduling problem, examples of practical applications
Classification of scheduling problems
Integer Linear Programming formulations
Single machine scheduling: computational complexity, heuristic and exact algoritms
Parallel machine scheduling: exact, heuristic and approximation algorithms
Relationships with basic Combinatorial Optimization problems
Optimization problems in Project Scheduling
Job Shop scheduling: formulations, heuristic and exact algorithms

Learning Outcomes (Dublin Descriptors)

On successful completion of this course, the student should

Acquire knowledge of Machine Scheduling problems, their classification in terms of computational complexity and algorithmic techniques developed for their solution. Acquire the fundamentals of optimization methods for project management.
Acquire the ability to recognize Machine Scheduling problems in different application contexts, such as computer science, industrial engineering and management, and to identify effective solution paradigms.
Acquire autonomy in modeling and algorithmic choices for complex problems related to scheduling and project management.
Being able to hold a conversation and to read texts on topics related to the modeling of scheduling problems and the evaluation of algorithms for their solution
Acquire skills upgrading flexible knowledge and skills in the field of scheduling problems that arise in various areas, such as computer science, industrial engineering and management

Prerequisites and Learning Activities

basic elements of computational complexity, linear programming and network flows

Assessment Methods and Criteria

a paper test concerning with theoretical or computational exercises; an oral test, accessible only with a sufficient grade at the paper test, about general machine scheduling theoretical issues

Textbooks

Michael Pinedo, Scheduling Theory, Algorithms, and Systems , Prentice Hall.

Internet Resources

Homepage:

http://ns.di.univaq.it/~oil/didattica/corsi/so/somain_dx.htm

Course page updates

This course page is available (with possible updates) also for the following academic years:

To read the current information on this course, if it is still available, go to the university course catalogue .

Course information last updated on: 02 novembre 2016, 16:07