A university course timetabling using genetic algorithm / (Record no. 449)

MARC details
000 -LEADER
fixed length control field 02157nam a2200241 4500
001 - CONTROL NUMBER
control field UPMIN-00000010146
003 - CONTROL NUMBER IDENTIFIER
control field UPMIN
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230206172931.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230206b |||||||| |||| 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 2004
Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) A64 O39
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Oguis, GB Winston R.
9 (RLIN) 2139
245 00 - TITLE STATEMENT
Title A university course timetabling using genetic algorithm /
Statement of responsibility, etc. GB Winston R. Oguis
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. 2004
300 ## - PHYSICAL DESCRIPTION
Extent 46 leaves
502 ## - DISSERTATION NOTE
Dissertation note Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2004
520 3# - SUMMARY, ETC.
Summary, etc. Timetabling is an assignment-type problem that deals with properly listing university programs. It is classified into two types: examination timetabling and course timetabling. Whichever timetabling it is, this involves two types of constraints: s Oft and hard. Hard constraints are constraints that should always be satisfied by a timetable while soft constraints are only optional but desirable whenever satisfied. This study employed genetic algorithm, a meta-heuristics method that simulates the biological process of cell division and replication as observed in cellular mitosis. This algorithm involves several sub-algorithms such as data recombination, mutation, evaluation, and the generation of a new population of timetables. These algorithms were the applied on the data obtained from the College of Science and Mathematics (CSM) in the University of the Philippines in Mindanao as a timetabling problem. A total of thirty (30) timetables was obtained from the application of the algorithm. The raw data that was obtained from the University was translated into vector codes to facilitate checking of conflicts and mapped into a matrix. Following the algorithm created, manual manipulation as then employed to obtain the succeeding timetables. An evaluation function was created based on the set of hard and soft constraints and was maximized. Thus, a genetic algorithm CSM was formulated and implemented for producing feasible populations of timetables.
658 ## - INDEX TERM--CURRICULUM OBJECTIVE
Main curriculum objective Undergraduate Thesis
Curriculum code AMAT200,
Source of term or code BSAM
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
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Status Collection Home library Current library Shelving location Date acquired Source of acquisition Accession Number Total Checkouts Full call number Barcode Date last seen Price effective from
    Library of Congress Classification   Not For Loan Preservation Copy University Library University Library Archives and Records 2005-03-22 donation UAR-T-gd514   LG993.5 2004 A64 O39 3UPML00021482 2022-09-21 2022-09-21
    Library of Congress Classification   Not For Loan Room-Use Only College of Science and Mathematics University Library Theses 2005-03-01 donation CSM-T-gd1208   LG993.5 2004 A64 O39 3UPML00011305 2022-09-21 2022-09-21
 
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