The aim of studying and bibliography

The main aim of study: Student after the course is able to formulate and solve the optimization problem, and interpret the correctness of the results.

The general information about the module: The module is realized in the second semester. The module includes 18 hours of laboratories. The module ends with a credit. The optimization course was developed especially for specialists in the field of pharmacy. It has been expanded to a models describing the production using batch processes.

Bibliography required to complete the module

Bibliography used during lectures

1	J. Jeżowski, A. Jeżowska	Wprowadzenie do optymalizacji matematycznej w inżynierii chemicznej i procesowej	Oficyna Wydawnicza Politechniki Rzeszowskiej.	2011
2	J. Jeżowski, A. Jeżowska	Optymalizacja procesów i aparatów. Wybrane problemy z zakresu inżynierii chemicznej i procesowej	Oficyna Wydawnicza Politechniki Rzeszowskiej.	2011
3	J. Jeżowski, A. Jeżowska	Optymalizacja systemów procesowych	Oficyna Wydawnicza Politechniki Rzeszowskiej.	2011
4	R. Krupiczka, H. Merta	Optymalizacja Procesowa	Wydawnictwo Politechniki Śląskiej, Gliwice .	1998
5	St. Sieniutycz	Optymalizacja w inżynierii procesowej	WNT, Warszawa.	1991

Bibliography used during classes/laboratories/others

1	J. Jeżowski, A. Jeżowska	Optymalizacja systemów procesowych	Oficyna Wydawnicza Politechniki Rzeszowskiej.	2011
2	J. Jeżowski, A. Jeżowska	Wprowadzenie do optymalizacji matematycznej w inżynierii chemicznej i procesowej	Oficyna Wydawnicza Politechniki Rzeszowskiej.	2011
3	J. Jeżowski, A. Jeżowska	Optymalizacja procesów i aparatów.	Oficyna Wydawnicza Politechniki Rzeszowskiej.	2011

Bibliography to self-study

1

T.F. Edgar, D.M. Himmelblau, L. Lasdon

Optimization of chemical processes

McGraw-Hill.

2001

Basic requirements in category knowledge/skills/social competences

Formal requirements: registration for the semester

Basic requirements in category knowledge: mathematics - the notion of derivative, knowledge of chemical engineering processes

Basic requirements in category skills: computer skills at a basic level, the basics of Microsoft Excel, skills to critically analyze received results

Basic requirements in category social competences: ability to solve problems independently and in team

Module outcomes

MEK	The student who completed the module	Types of classes / teaching methods leading to achieving a given outcome of teaching	Methods of verifying every mentioned outcome of teaching	Relationships with KEK	Relationships with PRK
01	The student knows the basic concepts of mathematical optimization.	Laboratory, interactive lecture	the practical credit	K_W02++ K_W12+ K_U06++ K_U11+ K_U15+ K_K01++	P7S_KK P7S_UK P7S_UW P7S_WG
02	Student can identify the problem and select an appropriate method to address it.	problem laboratory, an individual project, the team project	report on the design, performance monitoring, oral speech	K_W02+ K_W03+ K_W12++ K_U07+ K_U11+ K_U15+ K_K01+	P7S_KK P7S_UW P7S_WG
03	Students can declare the problem in a computer program and solve it.	problem laboratory	observation of performance	K_W02++ K_W03++ K_W12++ K_U06+++ K_U07+++ K_U11+++ K_U15++ K_K01++	P7S_KK P7S_UK P7S_UW P7S_WG

Attention: Depending on the epidemic situation, verification of the achieved learning outcomes specified in the study program, in particular credits and examinations at the end of specific classes, can be implemented remotely (real-time meetings).

The syllabus of the module

Sem.	TK	The content	realized in	MEK
2	TK01	Optimality criteria in chemical technology.	L01	MEK01 MEK03
2	TK02	Formulation of mathematical optimization problems for industrial cases. Mathematical models of processes and apparatus, the identification of model parameters.	L02,L06, L07	MEK01 MEK02 MEK03
2	TK03	Mathematical optimization of functions of several variables without restrictions. Numerical optimization of functions of one variable without restriction.	L02	MEK01
2	TK04	Mathematical optimization of functions of several variables with equality and inequality constraints.	L01	MEK01 MEK02
2	TK05	Linear programming.	L02	MEK01 MEK02
2	TK06	Selected problems of nonlinear programming.	L03	MEK01 MEK02
2	TK07	Fundamentals of mathematical programming with discrete variables.	L05, L06	MEK01 MEK02
2	TK08	Evolutionary optimization method	L010	MEK01 MEK02
2	TK09	Formulation of optimization mathematical examples.	L01,L02,L03,L04,L08,L09,L11-L13	MEK02
2	TK10	The rules of using a computer program supporting mathematical optimization.	L01,L02,L10	MEK02 MEK03
2	TK11	Formulation of optimization problems in the field of process engineering and bioprocess, and their solution by known programs.	L04	MEK02 MEK03
2	TK12	Modeling of batch processes	L06, L07

The student's effort

The type of classes	The work before classes	The participation in classes	The work after classes
Laboratory (sem. 2)	The preparation for a Laboratory: 10.00 hours/sem.	contact hours: 18.00 hours/sem.	Finishing/Making the report: 12.00 hours/sem. Others: 10.00 hours/sem.
Advice (sem. 2)
Credit (sem. 2)		The written credit: 1.00 hours/sem.

The way of giving the component module grades and the final grade

The type of classes	The way of giving the final grade
Laboratory	The formulation of the problem, solve it and present the results as a report and an oral description - OL
The final grade	Final mark (FM): FM = w*OL w - a factor related to the term credit or examination, w = 1,0 the first term,w = 0,9 the second term, w = 0,8 a third term. While rounding average, the following rules are apply: to 3,30 – dst (3,0); 3,31 - 3,75 – +dst (3,5); 3,76 - 4,25 – db (4,0); 4,26 - 4,70 – +db (4,5); from 4,71 – bdb (5,0).

Sample problems

Required during the exam/when receiving the credit
(-)

Realized during classes/laboratories/projects
(-)

Others
(-)

Can a student use any teaching aids during the exam/when receiving the credit : no

The contents of the module are associated with the research profile: yes

1

D. Foo; G. Poplewski

An extended corner point method for the synthesis of flexible water network

2021