Robust COA planning with varying durations

Author

Tang, Luohao ; Zhu, Cheng ; Zhang, Weiming ; Liu, Zhong

Author_Institution

Sci. & Technol. on Inf. Syst. Eng. Lab., Nat. Univ. of Defense & Technol., Changsha, China

fYear

2011

fDate

15-17 Sept. 2011

Firstpage

433

Lastpage

437

Abstract

COA (Course of Action) planning involves resource allocation and task scheduling. Traditionally, this problem is tackled with the assumption that task duration is constant and with the objective to minimize the makespan. In contrast to this, this paper assumes task duration can vary in a time interval and the objective is to maximize the RM (Robustness Measure) given the deadline, which makes sense to deal with the duration uncertainty. A COA planning method based on GA (Genetic Algorithm) and STN (Simple Temporal Network) is proposed and a COA planning instance is presented to illustrate the usefulness of this method.

Keywords

computational complexity; genetic algorithms; military systems; planning; resource allocation; scheduling; COA planning instance; course-of-action planning; genetic algorithm; makespan minimization; military COA planning; resource allocation; robustness measure; simple temporal network; task scheduling; Biological cells; Genetic algorithms; Resource management; Robustness; Schedules; Uncertainty; COA planning; GA; Simple Temporal Network; varying durations;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-61284-203-5

Type

conf

DOI

10.1109/CCIS.2011.6045104

Filename

6045104