TY - JOUR
T1 - Metaheuristic methods in hybrid flow shop scheduling problem
AU - Choong, Florence Chiao Mei
AU - Phon-Amnuaisuk, Somnuk
AU - Alias, Mohammad Yusoff
PY - 2011/9
Y1 - 2011/9
N2 - Memetic algorithms are hybrid evolutionary algorithms that combine global and local search by using an evolutionary algorithm to perform exploration while the local search method performs exploitation. This paper presents two hybrid heuristic algorithms that combine particle swarm optimization (PSO) with simulated annealing (SA) and tabu search (TS), respectively. The hybrid algorithms were applied on the hybrid flow shop scheduling problem. Experimental results reveal that these memetic techniques can effectively produce improved solutions over conventional methods with faster convergence.
AB - Memetic algorithms are hybrid evolutionary algorithms that combine global and local search by using an evolutionary algorithm to perform exploration while the local search method performs exploitation. This paper presents two hybrid heuristic algorithms that combine particle swarm optimization (PSO) with simulated annealing (SA) and tabu search (TS), respectively. The hybrid algorithms were applied on the hybrid flow shop scheduling problem. Experimental results reveal that these memetic techniques can effectively produce improved solutions over conventional methods with faster convergence.
U2 - 10.1016/j.eswa.2011.01.173
DO - 10.1016/j.eswa.2011.01.173
M3 - Article
SN - 0957-4174
VL - 38
SP - 10787
EP - 10793
JO - Expert Systems with Applications
JF - Expert Systems with Applications
IS - 9
ER -