MULTI-OBJECTIVE OPTIMIZATION APPROACH TO OPERATIONAL PLANNING FOR THE ELECTRONIC WARFARE FORCE85 views
Keywords:Guidance technique; Surrogate model; Multi-objective optimization; M-K-RVEA; M-CSEA.
In the stage of organizing and preparing for the campaign, the director of electronic warfare prepares a operational plan of the force, which determines the tasks for electronic warfare units. Tasks require the use of resources in terms of people and equipments. Tasks can be performed in parallel but are bound to each other. A plan is considered good if it simultaneously achieves optimal with basic objectives including: the shortest total execution time, the highest implementation efficiency and the average rate of resource used is the lowest. The paper proposes the multi-objective optimization approach to the operational planning problem and applies surrogate-assisted evolutionary algorithms with the adaptive guidance technique to find the optimal solutions.
. Ganguly S., "Multi-objective planning for reactive power compensation of radial distribution networks with unified power quality conditioner allocation using particle swarm optimization", IEEE Transactions on Power Sys-tems 29.4 (2014), pp.1801-1810.
. Kuo T. C., Chen H. M., Liu C. Y., Tu J. C., Yeh T. C., "Applying multi-objective planning in low-carbon product design", International Journal of Precision Engineering and Manufacturing 15.2 (2014), pp. 241-249.
. Hu X., Zhang H., Chen D., Li Y., Wang L., Zhang F., Cheng H., "Multi-objective planning for integrated energy systems considering both exergy efficiency and economy", Energy 197 (2020), pp. 117-155.
. Dinh N.D., Long N., Hoai N.X., "A guidance method for robustness surrogate assisted multi-objective evolutionary algorithms", Journal of Research and Development on Information and Communication Technology, vol 2021 no 1 (2021), pp. 1-18.
. Chugh T., Jin Y., Hakanen J., Miettinen K., "K-RVEA: A Kriging-assisted evolutionary algorithm for many-objective optimization", Scientific Computing, no.B, 2 (2016).
. Pan L., He C., Tian Y., Wang H., Zhang X., Jin Y., "A classification-based surrogate-assisted evolutionary algorithm for expensive many-objective optimization", IEEE Transactions on Evolutionary Computation, 23.1 (2018), pp.74-88.
. Audet C., Bigeon J., Cartie D., Digabel S. L., Salomon L., "Performance indicators in multi-objective optimization", European Journal of Operational Research, vol 292 (2021), pp.397-422.