TY - JOUR
T1 - Application of a genetic algorithm to staff scheduling in retail sector
AU - Zolfaghari, Saeed
AU - Quan, Vinh
AU - El-Bouri, Ahmed
AU - Khashayardoust, Maryam
PY - 2010
Y1 - 2010
N2 - A Genetic Algorithm (GA) is developed for the retail staff scheduling problem. The proposed algorithm is implemented and compared with a conventional integer programming branch-and-bound approach. The performance of the algorithm is tested on six real-world problems. A sensitivity analysis is carried out on three problems for two genetic parameters: population size and mutation rate. Using statistical analysis, the effects of these parameters on the solution quality and computational times are studied. The comparative study shows that GA can produce near-optimal solutions for all of the test problems, and for half of them, it is more successful than the branch-and-bound method.
AB - A Genetic Algorithm (GA) is developed for the retail staff scheduling problem. The proposed algorithm is implemented and compared with a conventional integer programming branch-and-bound approach. The performance of the algorithm is tested on six real-world problems. A sensitivity analysis is carried out on three problems for two genetic parameters: population size and mutation rate. Using statistical analysis, the effects of these parameters on the solution quality and computational times are studied. The comparative study shows that GA can produce near-optimal solutions for all of the test problems, and for half of them, it is more successful than the branch-and-bound method.
KW - GA
KW - Genetic Algorithm
KW - Integer programming
KW - Labour scheduling
KW - Meta-heuristics
KW - Service operations management
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U2 - 10.1504/IJISE.2010.029755
DO - 10.1504/IJISE.2010.029755
M3 - Article
AN - SCOPUS:77954867476
SN - 1748-5037
VL - 5
SP - 20
EP - 47
JO - International Journal of Industrial and Systems Engineering
JF - International Journal of Industrial and Systems Engineering
IS - 1
ER -