Authors: Minh-Tuan Nguyen; Thang Cao
Addresses: Strategy and Joint Force, Joint and Operations Analysis Division, Defence Science and Technology Group, Australia ' Land Capability Analysis, Joint and Operations Analysis Division, Defence Science and Technology Group, Australia
Abstract: This paper utilises Bayesian network (BN), multi-criteria decision making (MCDM), and multi-objective evolutionary algorithms (MOEA) to present a hybrid decision making model for evaluating and optimising the operational impact of different land combat vehicle (LCV) system specifications and configurations. BN is employed to establish a qualitative and quantitative representation of the relations between the variables of the model and calculate standard values of uncertain LCV capabilities like survivability, lethality, etc. MCDM is adopted to integrate the influence of LCV capabilities and calculate the utility value of the selected options. An interactive analysis tool using MOEA is developed to manage the combinatorial nature of the number of LCV system options available and to help the decision maker to avoid any arbitrary selection of sub-optimum baseline vehicles.
Keywords: Bayesian network; BN; multi-criteria decision making; MCDM; analytic hierarchy process; AHP; data visualisation; data analysis; Pareto optimisation; multi-objective evolutionary algorithms; MOEA.
International Journal of Applied Decision Sciences, 2019 Vol.12 No.4, pp.337 - 360
Available online: 07 May 2019 *Full-text access for editors Access for subscribers Purchase this article Comment on this article