Title :
An insertion mutation operator for solving project scheduling problem
Author :
Nazeri, Zeinab ; Khanli, Leili Mohammad
Author_Institution :
Comput. Sci. Dept., Univ. of Tabriz, Tabriz, Iran
Abstract :
Project scheduling problem is to determine the schedule of allocating resources to activities so as to balance the total cost and completion time of the project. The problem has been studied considering certain and uncertain activity duration times. In project scheduling with certain activity duration times, the duration of activities are previously obvious while in the project scheduling with uncertain activity duration times, the duration of each activity is considered to be uncertain. For each kind of project scheduling problem, various optimization methods such as genetic algorithm have been used. In this paper, an insertion mutation is proposed for solving the project scheduling problem with uncertain activity duration times which ensures earlier convergence to the optimal solution if being added to the mutation operator of genetic algorithm.
Keywords :
convergence; genetic algorithms; mathematical operators; project management; resource allocation; scheduling; certain activity duration time; completion time; convergence; genetic algorithm; insertion mutation operator; optimal solution; optimization methods; project scheduling problem; resource allocation; total cost; uncertain activity duration time; Biological cells; Genetic algorithms; Processor scheduling; Scheduling; Sociology; Statistics; Stochastic processes; genetic algorithm (GA); insertion mutation; project scheduling problem;
Conference_Titel :
Intelligent Systems (ICIS), 2014 Iranian Conference on
Conference_Location :
Bam
Print_ISBN :
978-1-4799-3350-1
DOI :
10.1109/IranianCIS.2014.6802537