Title :
A multi-objective optimization approach for resource assignment and task scheduling problem: Application to maritime domain awareness
Author :
Dridi, Olfa ; Krichen, Saoussen ; Guitouni, Adel
Author_Institution :
LARODEC Lab., Univ. of Tunis, Bardo, Tunisia
Abstract :
Large volume surveillance missions are characterized by the employment of mobile and fixed surveillance assets to a large geographic operation area in order to perform surveillance activities. Finding efficient management solutions should be investigated to optimize assets allocation and tasks achievement. In this paper, we propose to model this optimization problem as a multi-objective, multi-mode assignment and scheduling problem. Resources are to be assigned to accomplish the tasks. Then, surveillance tasks should be scheduled onto successive periods. The problem is designed to consider two conflicting objective functions: minimizing the makespan and minimizing the total cost. As the problem is NP-Hard, a bi-colony ant based approach is proposed. The empirical validation is done using a simulation environment Inform Lab. The experimental results show that the computational time remains polynomial with respect to the problem´s size.
Keywords :
ant colony optimisation; computational complexity; marine safety; minimisation; resource allocation; scheduling; surveillance; Inform Lab; NP-hard problem; asset allocation optimization; bicolony ant-based approach; empirical validation; fixed surveillance assets; geographic operation area; large-volume surveillance missions; makespan minimization; maritime domain awareness; mobile surveillance assets; multiobjective-multimode resource assignment and task scheduling problem; objective function conflicts; polynomial computational time; simulation environment; task achievement optimization; total-cost minimization; Job shop scheduling; Optimal scheduling; Processor scheduling; Schedules; Surveillance; Assignment and scheduling problem; Bi-colony ant approach; Large volume surveillance missions;
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
DOI :
10.1109/CEC.2012.6256501