In the combat management systems, mathematical and optimization models have significant impact to find good solutions for fire allocation and scheduling problems. In this paper, a linear integer programming model has been developed for a fire allocation and scheduling problems the aim of which was to maximize the expected value of the target distruction and strategic realms protection and efficient use of weapons by considering the operational constraints for weapon allocation. Since the available operation research solvers can not find the optimal solution of this problem in the large scale sizes, two metaheuristics based on genetic algorithm and chaotic particle swarm optimization was developed. Finally, based on randomnly generated test instances and extensive computation results, the performance of the developed algorithms was evaluated. The computational experiments reveal that the developed chaotic particle swarm optimization algorithm is more efficient especially in the limited and short CPU run time.
Peymankar, M., & Baloucian, S. (2018). Modeling and Solution of Fire Allocation and Scheduling Problem of Distributed Sites. Journal of Advanced Defense Science & Technology, 9(4), 487-504.
MLA
Mahbubeh Peymankar; Saeed Baloucian. "Modeling and Solution of Fire Allocation and Scheduling Problem of Distributed Sites". Journal of Advanced Defense Science & Technology, 9, 4, 2018, 487-504.
HARVARD
Peymankar, M., Baloucian, S. (2018). 'Modeling and Solution of Fire Allocation and Scheduling Problem of Distributed Sites', Journal of Advanced Defense Science & Technology, 9(4), pp. 487-504.
VANCOUVER
Peymankar, M., Baloucian, S. Modeling and Solution of Fire Allocation and Scheduling Problem of Distributed Sites. Journal of Advanced Defense Science & Technology, 2018; 9(4): 487-504.
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