The Crane Scheduling Problem and the Hybrid Intelligent Optimization Algorithm GASA

Author

Qing, Sun Jun ; Ping, Li ; Mei, Han

Author_Institution

Tianjin Univ. of Technol., Tianjin

fYear

2007

Firstpage

92

Lastpage

96

Abstract

In the operations of the container ports, quay crane scheduling is critical to the operational efficiency of a container terminal. In this paper we present an improved model for the quay crane scheduling problem and solve this mix integer programming model by the genetic algorithm GA and the hybrid intelligent optimization algorithm GASA respectively. Compared with the genetic algorithm, the hybrid intelligent optimization algorithm GASA increases the diversity of the individuals, accelerates the evolution process and avoids sinking into the local minimal solution.

Keywords

containers; cranes; genetic algorithms; integer programming; scheduling; simulated annealing; container port; container terminal; genetic algorithm; hybrid intelligent optimization algorithm; integer programming model; quay crane scheduling problem; simulated annealing; Acceleration; Automation; Computer science; Containers; Cranes; Genetic algorithms; Linear programming; Processor scheduling; Scheduling algorithm; Sun; genetic algorithm; hybrid intelligent optimization algorithm GASA; quay crane scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2007. CCC 2007. Chinese

Conference_Location

Hunan

Print_ISBN

978-7-81124-055-9

Electronic_ISBN

978-7-900719-22-5

Type

conf

DOI

10.1109/CHICC.2006.4347572

Filename

4347572