MARC details
| 000 -LEADER |
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| fixed length control field |
02246nam a22002773a 4500 |
| 001 - CONTROL NUMBER |
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| control field |
UPMIN-00004810091 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
UPMIN |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20230208105702.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
230208b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Transcribing 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) |
A64 P35 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Palma, Hananeel P. |
| 9 (RLIN) |
2162 |
| 245 ## - TITLE STATEMENT |
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| Title |
Particle swarm optimization for an uncapacitated facility location problem / |
| Statement of responsibility, etc. |
Hananeel P. Palma |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Date of publication, distribution, etc. |
2010 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
53 leaves. |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2010 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
The uncapacitated facility location problem (FLP) is a mathematical way to optimally locate facilities within a set of candidates such that each facility has no capacity limit in satisfying the requirements of a given set of clients. Particle swarm optimization (PSO) is a population-based optimization technique which operates on a population of potential solutions applying an information sharing approach to produce better and better approximations to a solution. Though hybrid methods have been reported to produce better results, this study used PSO in a stand-alone mode to determine first its potential in finding solutions for uncapacitated FLP particularly when applied to real world data. First, a successful mapping between the method and the problem was established. Then a minimization fitness function to evaluate the solutions was defined which involves penalty for every violated constraint. Upon implementation of the method for the problem, best parameter values to solve the problem were achieved. Results showed that applying PSO for the problem yielded better facility locations compared to the existing ones. However, although these results showed that PSO is a promising method to solve this particular problem, further studies are still needed to improve the results such as by reducing the values of the parameters to fit the small-scaled search space of the data. |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Facility location problem |
| 9 (RLIN) |
2163 |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Particle swarm optimation |
| 9 (RLIN) |
2164 |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Uncapacitated facility location problem |
| 9 (RLIN) |
2165 |
| 658 ## - INDEX TERM--CURRICULUM OBJECTIVE |
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| 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) |
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| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Thesis |
