Operational Research

• Number of credits allocated

• Name of lecturer / lecturers : Dr Agapios Platis

---------------------------------------------------------------------------------------------------------------------------------------

• Description :

The objective of this course is to provide students with the appropriate basic tools of Operations Research for the decision support in management and operations systems. A wide range of OR methodologies is approached with emphasis in applications.

---------------------------------------------------------------------------------------------------------------------------------------

--------------------------------------------------------------------------------------------------------------------------------------

• Prerequisites :

None

• Module Contents ( Syllabus) :

Introduction to operations research, linear programming, modelling, Simplex method, Big M method, duality, sensitivity analysis. IOR Tutorial and Excel Solver. Network optimization, graphs and networks, the shortest path, minimum spanning trees, maximum flow problem, minimal cost flow problem. Dynamic Programming. System Reliability. Elements of stochastic modelling.

• Recommended Reading :

Α) Principal Reference :

Notes are provided

Β) Additional References :

Basic Reference: F.S. Hillier, G. J. Lieberman, Introduction to Operations Research, 8th edition, Mc Graw-Hill International Edition

Operations Research: Applications and Algorithms

W. L. Winston

Duxbury Press, 2003

ISBN 978-0534380588

1440 Pages

Linear Programming

J.P. Ignizio, T.M. Cavalier

Prentice Hall, 1993

ISBN 978-0131837575

666 Pages

Operations Research: Principles and Practice

A. Ravindran, D.T. Philips, J.J. Solberg

Wiley, 1987

ISBN 978-0471086086

656 Pages

Linear Programming and Network Flows

M. S. Bazaraa, J.J. Jarvis, H.D. Sherall

Wiley, 1990

ISBN

684 Pages

Introduction to Operations Research Techniques

H. G. Daellenbach, J. A. George

Allyn and Bacon, 1983

ISBN 978-0205079742

750 Pages

Model Building in Mathematical Programming

H. P. Williams

Wiley, 1999

ISBN 978-0471997887

368 Pages

An Introduction to Management Science: Quantitative Approaches to Decision Making

D.R. Anderson, D.J. Sweeney, T.A. Williams, J.D. Camm, R.K. Martin

South-Western College Pub, 2011

ISBN 978- 1111532222

896 Pages

Tools for Thinking: Modelling in Management Science

M. Pidd

Wiley, 2003

ISBN 978-0470847954

332 Pages

Introduction to Management Science

B.W. Taylor,

Prentice Hall, 2009

ISBN 978-0136064367

840 Pages

A. Practical Introduction to Management Science

D.A. Waters

Addison Wesley Publishing Company, 1998

ISBN 978-0201178470

584 Pages

Introduction to Stochastic Processes,

E. Cinlar,

Prentice-Hall, Engenwood Cliffs, 1975

Probability and Statistics with Reliability, Queuing, and Computer Science Applications

K.S. Trivedi

Wiley-Interscience, 2002

ISBN 978-0471333418

830 Pages

Introduction to Probability Models

S.M. Ross

Academic Press, 2009

ISBN 978-0123756862

800 Pages

• Teaching Methods :

In class teaching, homework exercises, laboratory exercises, external invited speakers.

• Assessment Methods :

Project(20%), Final examination (80%)

• Language of Instruction :

Greek

• Module Objective (preferably expressed in terms of learning outcomes and competences):

- Understanding the basic concepts of mathematical programming.

- Understanding the basic concepts of mathematical modelling.

- Understanding and problem classification into linear programming, integer programming, etc.

- Modeling mathematical programming problems.

- Solving linear and dynamic programming problems

- Applying appropriate tools for solving linear programming problems.

- Applying the most suitable methodologies and respective algorithms to solve particular linear programming cases.

- Understanding the basic concepts of reliability engineering modelling.

- Understanding the basic concepts of reliability, availability and maintainability.