An adaptive hybrid algorithm for multi-mode resource-constrained project scheduling problems (Record no. 1607)

MARC details
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005 - DATE AND TIME OF LATEST TRANSACTION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 110107s2009 th uu|m rtt 0| a1eng d
035 ## - SYSTEM CONTROL NUMBER
System control number .b12088316
099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number AIT Thesis no.ISE-09-04
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Dao Duc Cuong
245 13 - TITLE STATEMENT
Title An adaptive hybrid algorithm for multi-mode resource-constrained project scheduling problems
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Pathum Thani, Thailand :
Name of publisher, distributor, etc. Asian Institute of Technology,
Date of publication, distribution, etc. 2009
300 ## - PHYSICAL DESCRIPTION
Extent 92 p. :
Other physical details ill.
490 1# - SERIES STATEMENT
Series statement Thesis ;
Volume/sequential designation no. ISE-09-04
500 ## - GENERAL NOTE
General note Submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Industrial and Manufacturing Engineering, School of Engineering Technology
520 ## - SUMMARY, ETC.
Summary, etc. This thesis focuses on the multi execution modes resource-constrained project scheduling problem with the objective of minimizing the project makespan. There might be more than one operating mode to perform an activity; each mode requires different amount of resources and related time duration. Besides, there are two types of resources: renewable and non-renewable. Adaptive particle swarm optimization and genetic algorithm are integrated in an algorithm called APSO-GA to solve the MRCPSP. The major motivation of APSO-GA is to use PSO to find the best priority of activities while GA is used to search for the combination mode of the activities. A potential solution of MRCPSP is represented as a pair of particle and chromosome and an active schedule can be achieved by transforming this representation by serial schedule method. In adaptive PSO algorithm, the two parameters evolved in velocity updating mechanism 12,cc can be self-adaptive depending on three factors, including their old values, the degree of acceleration and the swarm response. At the beginning of the searching procedure, the cognitive learning term plays a more important role than the social learning term in effect to particle{u2018}s velocity. The effect of cognitive learning term is decreased while that of social learning term is increased through the PSO iteration. Genetic algorithm is put inside the PSO algorithm, i.e. in each PSO iteration, a GA loop is used to search for a better mode combination of activities. The GA loop is performed until the exploring process cannot find a better combination of mode for current activities priority arrangement. Moreover, three difference types of GA crossover variants are applied to enhance the quality of searching procedure. The performance of the APSO-GA algorithm is investigated on standard instance sets. Experiment results show that the proposed adaptive PSO algorithm has proved the advantages over the non-adaptive one and the best GA crossover types is uniform crossover. The makespan results and computational time results of the proposed algorithm are also very competitive in comparing with others heuristics previously published.
502 ## - DISSERTATION NOTE
Dissertation note Thesis (M.Eng.) - Asian Institute of Technology, 2009
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Production scheduling
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer algorithms
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Voratas Kachitvichyanukul,
Relator term Chairperson
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Gong, Dah-Chuan,
Relator term Examination committee
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Huynh, Trung Luong,
Relator term Examination Committee
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element PetroVietnam,
Relator term Scholarship donor
810 2# - SERIES ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology.
Title of a work Thesis ;
Volume/sequential designation no. ISE-09-04
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-Text
Uniform Resource Identifier <a href="http://203.159.5.9/ait-thesis/detail.php?q=B03248 ">http://203.159.5.9/ait-thesis/detail.php?q=B03248 </a>
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998 ## - LOCAL CONTROL INFORMATION (RLIN)
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Cataloger's initials, CIN (RLIN) 110107
First date, FD (RLIN) m
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Koha item type 22-AIT Thesis (Replacement)
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Koha item type 40-Archives
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      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 17/08/2026 50.00   AIT Thesis no.ISE-09-04 30050120700934 17/08/2026 3 17/08/2026 22-AIT Thesis (Replacement)
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library Archives 17/08/2026     AIT Thesis no.ISE-09-04 30050160030689 17/08/2026 1 17/08/2026 40-Archives
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