000			03443nas|a2200397 a 4500
005			20260817161528.0
008			110110s2009 th uu|m rtt 0| a1eng d
035			_a.b12088456
099		9	_aAIT Thesis no.ISE-09-17
100	0		_aSuparat Wongnen
245	1	3	_aAn adaptive particle swarm optimization algorithm for multiobjective job shop scheduling problems
260			_aPathum Thani, Thailand : _bAsian Institute of Technology, _c2009
300			_a67 p. : _bill.
490	1		_aThesis ; _vno. ISE-09-17
500			_aSubmitted in partial fulfillment of the requirements for the degree of Master of Engineering in Industrial and Manufacturing Engineering, School of Engineering and Technology
520			_aThis research introduces an adaptive particle swarm optimization algorithm for multi objective job shop scheduling problems. The three objectives considered in this research are: minimize makespan, minimize total weighted earliness and minimize total weight tardiness. The objective is to find optimal or near optimal results with these objectives. The solution of multi objective cases will be represented in two ways as weight aggregating approach and Pareto optimization approach. The proposed algorithm uses an adaptive PSO which is approach to solve the problem. The parameter adaptation of PSO is focused on inertia weight and acceleration constants. In order to get high quality of solution the re-initialization strategy and local search and also applied in the proposed algorithm. The proposed algorithm is evaluated by using the benchmark problems provided by the OR-library and compared it with best known results from published works for both single and multi objective cases. The proposed PSO algorithm can find good solutions in both of single and multi objective cases in term of solution quality and computational time. However, the result from the proposed algorithm cannot performed better than 2ST-PSO in some cases because of the number of particles. Also, when the proposed algorithm use the same number of particles with 2ST-PSO, then the result performed better than 2ST-PSO in term of solution quality but take longer computational time.
502			_aThesis (M.Eng.) - Asian Institute of Technology, 2009
650		0	_aProduction scheduling
700	0		_aVoratas Kachitvichyanukul, _eChairperson
700	1		_aGong, Dah-Chuan, _eExamination committee
700	1		_aHuynh, Trung Luong, _eExamination Committee
710	2		_aAsian Institute of Technology Fellowship, _eScholarship donor
810	2		_aAsian Institute of Technology. _tThesis ; _vno. ISE-09-17
856			_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B03259
907			_a.b12088456 _bmnait _cu
902			_a240401
998			_b0 _c110110 _dm _ea _fu _g3
962			_a000:001:PDF:b1208845:000361:0:0:0:0:0:0 _tAbstract-AIT Thesis no.ISE-09-17 _vn
945			_lmnait
945			_lmnarc
942			_c22
942			_c40
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