Hybrid particle swarm optimization tabu-search (PSO-TS) approach applied to constrained engineering optimization problems / (Record no. 688)

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001 - CONTROL NUMBER
control field UPMIN-00000518099
003 - CONTROL NUMBER IDENTIFIER
control field UPMIN
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20221020160208.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 221020b |||||||| |||| 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 #0 - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) LG993.5 2007
Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) C6 M48
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Mesa, Armacheska Rivero.
245 ## - TITLE STATEMENT
Title Hybrid particle swarm optimization tabu-search (PSO-TS) approach applied to constrained engineering optimization problems /
Statement of responsibility, etc. Armacheska R. Mesa
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. 2007
300 ## - PHYSICAL DESCRIPTION
Extent 69 leaves.
502 ## - DISSERTATION NOTE
Dissertation note Thesis (BS Computer Science) -- University of the Philippines Mindanao, 2007
520 3# - SUMMARY, ETC.
Summary, etc. Many engineering design problems can be formulated as constrained optimization problems. There are several methods reported in literature that can solve many of these optimization design problems with constraints. Genetic algorithm, self-adaptive penalty approach and other evolutionary algorithms had been used to find the optimal solutions to these engineering problems. So far, particle swarm optimization has been the most effective method reported in literature to solve such problems. With the advent of the hybridization techniques to create efficient algorithms pure PSO was paired to several other heuristics and these hybrids were used to solve many optimization problems. Hence, a fast, intelligent meta-heuristic, Tabu Search (TS), was introduced to the pure PSO to solve engineering optimization problems. With the embedded hybridization, the study showed positive results returned by the PSO-TS hybrids and were better compared to the results of other algorithms reported in Hu et.al?s. (2003) and He and Wang?s paper (2006). It is well known that practical engineering optimization involves multiple, nonlinear and non-trivial constraints due to real world limitations. From an engineering standpoint, a better, faster, cheaper solution is always desired. In this study, the embedded hybrid performed well on all our engineering optimization problems tested
650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Optimization.
658 ## - INDEX TERM--CURRICULUM OBJECTIVE
Main curriculum objective Undergraduate Thesis
Curriculum code CMSC200,
Source of term or code BSCS
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 Koha item type
    Library of Congress Classification   Not For Loan Preservation Copy University Library University Library Archives and Records 2008-04-15 donation UAR-T-gd993   LG993.5 2007 C6 M48 3UPML00035011 2022-09-21 Thesis
    Library of Congress Classification   Not For Loan   College of Science and Mathematics University Library General Reference 2007-10-26 donation CSM-T-gd1770   LG993.5 2007 C6 M48 3UPML00012087 2022-09-21 Thesis
 
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