000			02745nam a22003253a 4500
001			UPMIN-00003300430
003			UPMIN
005			20230206171427.0
008			230206b |||||||| |||| 00| 0 eng d
040			_aDLC _cUPMin _dupmin
041			_aeng
090		0	_aLG993.5 2009 _bA64 N86
100			_aNuñez, Joey Marie Tragura. _92129
245			_aModified shuffled frog leaping algorithm application on the nurse scheduling problem in Davao Medical Center / _cJoey Marie Tragura Nuñez.
260			_c2009
300			_a72 leaves.
502			_aThesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2009
520	3		_aNurse scheduling problem (NSP) involves producing daily schedules for nurses over a given time horizon, considering hospital policies which must be satisfied to obtain feasible schedules. Shuffled frog leaping algorithm (SFLA) is a population-based search algorithm where a set of frogs is partitioned to memeplexes wherein local searches are performed. There is no found literature which applied SFLA to NSP. This study explored the applicability of SFLA to a NSP where the PSO-based local search was modified by using the genetic algorithm operators: uniform crossover and violation-directed mutation. A modified shuffled frog leaping algorithm (MSFLA solution representation was formulated that fits the nurse scheduling problem in Davao Medical Center, a government tertiary hospital in Southern Mindanao. Nurse aid and nurse schedules were separately represented. A fitness function was developed which minimizes the penalties obtained by a schedule. Parameters were set to 30 individuals in a population, 6 memeplexes, 10 memeplex iterations, 1000 shuffling iterations, 100% crossover and mutation occurrence rates and 2% mutation rate. The MSLA produced feasible schedules but it failed to give the required number of day-off, did not distribute shifts fairly to nurses and violated the allowable conservative shift types. The schedules generated by the MSFLA were compared to the schedules done manually and by the Global Programming (GP) method of Sebastian (2007). The schedules generated by the MSFLA are better than the manual method. The GP method outperformed it but the nurse schedule of this method is not feasible.
650	1	7	_aSwap mutation. _91358
650	1	7	_aShuffled frog leaping algortihm. _92130
650	1	7	_aNurse scheduling. _91357
650	1	7	_aUnifrom crossover. _92131
650	1	7	_aViolation-directed mutation. _92132
650	1	7	_aMSFLA (Modified shuffled frog leaping algortihm). _92133
650	1	7	_aGA (Genetic algorithm) operators. _92134
658			_aUndergraduate Thesis _cAMAT200, _2BSAM
905			_aFi
905			_aUP
942			_2lcc _cTHESIS
999			_c2266 _d2266