MARC details
| 000 -LEADER |
|---|
| fixed length control field |
01988nam a2200313 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
UPMIN-00000014635 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
UPMIN |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20221205112232.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
221205b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Transcribing agency |
UPMin |
| Modifying agency |
upmin |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
LG993.5 2006 |
| Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) |
A64 C65 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Concepcion, Erick Castillo. |
| 9 (RLIN) |
343 |
| 245 00 - TITLE STATEMENT |
|---|
| Title |
Comparison of static and dynamic penalty functions for handling constraints in genetic algorithm applied to course timetabling for CSM in UPMin / |
| Statement of responsibility, etc. |
Erick Castillo Concepcion. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Date of publication, distribution, etc. |
2006 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
54 leaves |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Thesis, Undergraduate (BS Applied Mathematics) -- U. P. in Mindanao |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
This study presents an application of generic algorithm (GA) on university course timetabling problem using penalty functions were utilized as fitness function, penalizing only on the soft constraints since all hard constraints must be satisfied. One is static penalty function having a fixed penalty parameter in the entire optimization process, and dynamic penalty function where the penalty factors are dependent on the current generation. In comparing the solution between the best for static penalty and the best for dynamic penalty, the later has relatively lower constraint violation making that solution better than the static penalty. Thus, dynamic penalty function is a better performer than static penalty function as a fitness function in a GA optimization process, although the soft constraints were partitioned into equality and inequality constraints, it is not clear which among the constraints is more violated because they have a different degree of penalty |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Genetic algorithm. |
| 9 (RLIN) |
344 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Timetabling. |
| 9 (RLIN) |
345 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Timetbaling |
| General subdivision |
Courses. |
| 9 (RLIN) |
346 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Static functions. |
| 9 (RLIN) |
347 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Dynamic functions. |
| 9 (RLIN) |
348 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Handling constraints. |
| 9 (RLIN) |
349 |
| 658 ## - INDEX TERM--CURRICULUM OBJECTIVE |
|---|
| Main curriculum objective |
Undergraduate Thesis |
| Curriculum code |
AMAT200 |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) |
|---|
| a |
fi |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) |
|---|
| a |
UP |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Thesis |
