MARC details
| 000 -LEADER |
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| fixed length control field |
02357nam a22003013a 4500 |
| 001 - CONTROL NUMBER |
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| control field |
UPMIN-00004810100 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
UPMIN |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20221018111854.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
221018b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
DLC |
| Transcribing agency |
UPMin |
| Modifying agency |
upmin |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
eng |
| 090 #0 - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
LG993.5 2010 |
| Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) |
C6 M36 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Manluctao, Clarice Germin T. |
| 245 ## - TITLE STATEMENT |
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| Title |
Artificial bee colony algorithm with penalty function constraint handling method applied to cutting stock problem / |
| Statement of responsibility, etc. |
Clarice Germin T. Manluctao |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Date of publication, distribution, etc. |
2010 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
81 leaves. |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2010 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
Most real-world optimization are faced with constraints which must be satisfied with an acceptable solution. There are lot of proven methods that can solve many of these optimization problems such as Evolutionary Programming(EP), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). These methods are also called heuristics. A new metaheuristic study of Karaboga (2005), which is called Artificial Bee Colony (ABC) algorithm, is originally designed to solve unconstrained problems. The algorithm, as Karaboga (20050 describes it, is simple and flexible. Since most of the problems are subjected to constraints, in this study the original ABC algorithm was incorporated with a constraint handling method called penalty function. Hence, a modified Artificial Bee Colony algorithm is introduced to solve constrained problems. To test the feasibility of the modified algorithm, it was applied to a one dimensional cutting stock problem. Based on the study conducted, the ABC algorithm integrated with a constraint handling method returned good results to all the rest problems presented in the study. These results were compared to a study made by Lacsama (2008) called Modified shuffle frog leaping algorithm (MSFLA). The modified ABC gave better results than MSFLA for some of the test problems. The modified ABC algorithm also performed relatively fast in obtaining the best solutions for each of the test problem |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Artificial bee colony algorithm |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Constraints |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Cutting stock problem |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Metaheuristic |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Penalty function |
| 658 ## - INDEX TERM--CURRICULUM OBJECTIVE |
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| Main curriculum objective |
Undergraduate Thesis |
| Curriculum code |
CMSC200, |
| Source of term or code |
BSCS |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) |
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| a |
Fi |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) |
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| a |
UP |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Thesis |
