Abstract—Integrated scheduling of handling/storage
equipment in container terminals is an NP-hard problem which
has been studied during past two decades consciously. Genetic
algorithms (GAs) have been applied for this optimization
problem in many researches. However, the GA is vulnerable to
trap in a local optima (results in premature convergence). In
this paper a fuzzy logic controller (FLC) is designed to improve
the performance of a GA in optimization of integrated
scheduling of handling/storage equipment in automated
container terminals. The FLC controls crossover and mutation
rates of the GA during its generations, which are the main
control parameters of the GA to avoid the premature
convergence. The numerical results for the small size test cases
solved by using the proposed fuzzy genetic algorithm show that
solutions found by this algorithm are 2.5% better than the
solutions found by the GA. Studies are continuing for better
performance of the proposed FGA.
Index Terms—Integrated scheduling, fuzzy logic controller,
genetic algorithm, fuzzy genetic algorithm.
Seyed Mahdi Homayouni is with the Department of Industrial
Engineering, Lenjan Branch, Islamic Azad University, Isfahan, Iran (e-mail:
homayouni@ iauln.ac.ir).
Sai Hong Tang is with the Department of Mechanical & Manufacturing
Engineering, Faculty of Engineering, Universiti Putra Malaysia, Malaysia
(e-mail: saihong@upm.edu.my).
[PDF]
Cite: Seyed Mahdi Homayouni, Senior Member, IEDRC and Sai Hong Tang, "A Fuzzy Genetic Algorithm for Scheduling of
Handling/Storage Equipment in Automated Container
Terminals," International Journal of Engineering and Technology vol. 7, no. 6, pp. 497-501, 2015.
