Abstract
Industrial logistics plays a key role in industrial engineering. Since battle damage assessment and repair (BDAR) process is essentially military industrial logistics process, optimal decisions for operations management of BDAR are crucial to military industrial logistics planning. The purpose of this paper is to present a systematic procedure of optimal decisions for operations management of BDAR and form a framework of military industrial logistics data analytics. Based on war statistics from the collected historical real-world combat data, by classifying the damaged equipments into emergency group and non-emergency group, this study establishes three mathematical models on decision-making for operations management of BDAR, and presents resolutions to problems of optimized deployment, task allocation and selection of formation schemes for the resources in military industrial logistics system. Subsequently, an agent-based simulation model for military industrial logistics system is developed to demonstrate and verify the method. The results show that the method is feasible and effective.
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