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9.14S - Quantitative Methods for Business Decision Making

9.14S - Quantitative Methods for Business Decision Making

Quantitative Methods for Business Decision Making

Code: 9.14S

Semester: 9 / Year: 5 (Optional)

Teachers: Beligiannnis Grigorios

Course Web Page: https://eclass.upatras.gr/courses/DEAPT192/

Lectures hours (per week): 2

laboratory hours (per week): 1

Subject

  1. Distribution and Network Models
  2. IntegerLinearProgramming
  3. Inventory Models
  4. Simulation
  5. Decision Analysis
  6. Multicriteria Decision Making
  7. Dynamic Programming
  8. Computational Intelligence Algorithms|
  • Genetic Algorithms - GAs
  • Particle Swarm Optimization - PSO
  • Hill Climbing - HL
  • Simulating Annealing - SA
  • GreatDeluge– GD
  • Variable Neighbourhood Search – VNS
  • TabuSearch– TS

Educational Aims

The course offers the opportunity for students that will choose to attend it to get trained in specialized topics about solving problems of management science and operations research.
The purpose of this course is to present and explain the specialized way in which someone can apply modern quantitative and computational intelligence methods to solve specific difficult problems of management science and operations research. With the help of concrete examples and exercises students can understand in depth how to resolve various complex and specialized management science and operations research problems, while trained to be able to apply such techniques and tools in order to solve specialized real world problems.
This course enables students to gain specialized knowledge required to be able to analyze, design and implement modern quantitative and computational intelligence methods to solve difficult modern problems of management science and operations research.
By the end of this course the student will be able to:
  • understand thoroughly the principles, operation and how to apply quantitative and computational intelligence methods for solving management science and operations research problems
  • apply these methods to real problems from the field of economic and agronomic sciences, but also in their daily lives
  • use knowledge and understanding acquired in a manner that indicates a professional approach to their  work or profession
  • have competences typically demonstrated by developing and supporting arguments and solving problems within their field of knowledge
  • communicate information, ideas, problems and solutions to both specialist and non-specialist public
  • develop knowledge acquisition skills needed to continue to post graduate studies with a high degree of autonomy
  • gather and interpret relevant data (in their knowledge field) to form judgments that include reflection on relevant scientific issues
  • be able to use their knowledge, understanding and ability to solve problems in new or unfamiliar environment within broader (or multidisciplinary) context, related to their field
  • be able to communicate with clarity their conclusions, knowledge and reasoning in both specialized and non-specialized audience

Student Evaluation

Written examination after the end of the semester (100%) including:

  • Multiple-choice questions
  • Solving problems of designing and applying of quantitative and computational intelligence methodsto management science and operations research problems
  • Benchmarking theory elements

Bibliography

  1. Εισαγωγή στη Διοικητική Επιστήμη, B. W. Taylor III, Εκδόσεις Broken Hill Publishers L.t.d., 2018 (in Greek). 
  2. Διοικητική Επιστήμη: Ποσοτικές μέθοδοι για τη λήψη επιχειρηματικών αποφάσεων, D.R. Anderson, D.J. Sweeney, T.A. Williams, K. Martin, Εκδόσεις Κριτική, 2014 (in Greek).
  3. Introduction to Management Science (12th Edition) 12th  Edition, B. W. Taylor III , Hardcover: 864 pages, Publisher: Pearson; 12 edition (January 3, 2015), Language: English, ISBN-10: 0133778843.
  4. Quantitative Methods for Business, D.R. Anderson, D.J. Sweeney, T.A. Williams, K. Martin, Hardcover: 912 pages Publisher: Cengage Learning; 11th edition (February 11, 2009), Language: English, ISBN-10: 0324651813.
  5. Computational Intelligence: Principles, Techniques and Applications (Hardcover), Amit Konar, Hardcover: 708 pages, Publisher: Springer; 1 edition (May 31, 2005), Language: English, ISBN: 3540208984.
  6. Computational Intelligence in Economics and Finance (Advanced Information Processing), S. H. Chen, P. Wang, Paul P. Wang Hardcover: 508 pages, Publisher: Springer; 1 edition (April 11, 2006), Language: English, ISBN: 3540440984.