Course syllabus POV - Practice of Operations Research (ŠAVŠ - Sklad předmětů)

     Czech          English          

Course title: Practice of Operations Research
Semester: -- item not defined --
Course supervisor: doc. Ing. Jan Fábry, Ph.D.
Supervising department: Department of Logistics, Quality and Automotive Technology (ŠAVŠ)
Prerequisites for registration: Operational Research I or Operational Research II
Time allowance: full-time, 1/2 (hours of lectures per week / hours of seminars per week)
Type of study: usual
Form of teaching: lecture, seminar
Mode of completion and credits: Classified fulfillment of requirements (3 credits)
Course objective:
The aim of the course is to provide students experience in solving real problems of operations research, especially in the transportation and manufacturing, using computer technology and professional software.
 
Course methods: Problems solved in exercises are based on real problems, which were solved in the cooperation with practice. Students will solve these problems separately, using teacher's instructions and assistance, in optimization system MPL for Windows. For programming methods, VBA for Excel will be used.
 
Course content:
1.Solution of optimization problems in MPL for Windows. (allowance 2/2)
 
a.Introduction to the language of MPL for Windows.
b.Use of the system for basic optimization problems.

2.Case studies in transportation. (allowance 0/2)
 
a.Optimization of routes in revisions of electrical devices.

3.Case studies in transportation. (allowance 2/2)
 
a.Optimization of beer distribution.
b.Distribution of bread.

4.Case studies in transportation. (allowance 0/2)
 
a.Optimization in messenger companies.

5.Case studies in transportation. (allowance 2/2)
 
a.Placement of BUS timetables and maintenance of BUS stops.
b.Maintenance of tram lines and assignment of tram vehicles to depots.

6.Case studies in transportation. (allowance 0/2)
 
a.Optimization of transportation of agricultural commodities.

7.Case studies in transportation. (allowance 2/2)
 
a.Garbage collection.
b.Sweeping communications.

8.Case studies in manufacturing. (allowance 0/2)
 
a.Optimization of producing commodities in the glass company.

9.Case studies in manufacturing. (allowance 2/2)
 
a.Optimization of production in chemical industry.
b.Optimal scheduling in the machine works.

10.Case studies in manufacturing. (allowance 0/2)
 
a.Allocation of stocks in energy companies.
b.Allocation of machines in the mechanical plant.

11.Use of heuristic methods in case studies. (allowance 2/2)
 
a.Introduction to VBA for Excel.
b.Programming in VBA for Excel - data preparation and modification.

12.Use of heuristic methods in case studies. (allowance 0/2)
 
a.Programming selected methods in VBA for Excel - nearest neighbor algorithm for Traveling Salesman Problem.

 
Learning outcomes and competences:
After completing the course, student will be able to:
 
-Will analyse the real task, apply a suitable mathematical procedure and specialized software to solve it
-Will arrange the data obtained by analyzing the specified optimization task
-Will describe mathematical models for solving elementary optimization tasks
-Will select an appropriate mathematical model and advanced mathematical tools to solve illustrative optimization tasks

Teaching methods and workload (hours of workload):
Type of teaching methodDaily attendance
Direct teaching
     Attendance of lectures12 h
     Attendance of courses/seminars/tutorials24 h
Self-study
     Course reading and ongoing preparation10 h
     Ongoing evaluation40 h
     Composing of individual (seminar) work10 h
Total96 h
 
Assessment methods:
Requirement typeDaily attendance
Active lecture/seminar/workshop/tutorial participation90 %
Term paper10 %
Total100 %
 
Course completion:
Ongoing student's work on excercises, elaboration of homeworks / seminar work.
 
Support for combined/distance forms of study:
-- item not defined --
 
Reading list:
Basic:
Language of instruction: Czech
JABLONSKÝ, J. Operační výzkum.: Kvantitativní modely pro ekonomické rozhodování. 3rd ed. Praha: Professional Publishing, 2007. 323 p. ISBN 978-80-86946-44-3.
FÁBRY, J. Pokročilé matematické modely a metody.  [online]. 2017. URL: http://nb.vse.cz/~fabry/POV-prezentace.pdf.
Language of instruction: English
FÁBRY, J. Advanced Mathematical Models and Methods.  [online]. 2017. URL: http://nb.vse.cz/~fabry/POR-prezentace.pdf..

Recommended:
Language of instruction: Czech
PELIKÁN, J. Diskrétní modely v operačním výzkumu. 1st ed. Praha: Professional Publishing, 2001. 250 p. ISBN 80-86419-17-7.
JABLONSKÝ, J. Programy pro matematické modelování. Praha: Oeconomica, 2011. 258 p. ISBN 978-80-245-1810-7.
Language of instruction: English
TURBAN, E. -- MEREDITH, J R. Fundamentals of Management Science. Irwin: Homewood, 1988. ISBN 0-256-06256-0.

Study plans:
-- item not defined --
 
Run in the period of: WS 2019/2020, SS 2018/2019, WS 2018/2019, SS 2017/2018, SS 2016/2017, WS 2016/2017   (and older)
Course tutor: doc. Ing. Jan Fábry, Ph.D. (supervisor)
Teaching language: Czech, English
Room: Mladá Boleslav, Praha


Last modification made by doc. Ing. Jan Fábry, Ph.D. on 05/27/2019.

Type of output: