To analyze and optimize the weapon system of systems(WSOS)scheduling process,a new method based on robust capabilities for WSOS scheduling optimization is proposed.First,we present an activity network to represent the...To analyze and optimize the weapon system of systems(WSOS)scheduling process,a new method based on robust capabilities for WSOS scheduling optimization is proposed.First,we present an activity network to represent the military mission.The member systems need to be reasonably assigned to perform different activities in the mission.Then we express the problem as a set partitioning formulation with novel columns(activity flows).A heuristic branch-and-price algorithm is designed based on the model of the WSOS scheduling problem(WSOSSP).The algorithm uses the shortest resource-constrained path planning to generate robust activity flows that meet the capability requirements.Finally,we discuss this method in several test cases.The results show that the solution can reduce the makespan of the mission remarkably.展开更多
In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly an...In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis, reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.展开更多
基金supported by the National Key R&D Program of China(2018YFC0806900)the China Postdoctoral Science Foundation Funded Project(2018M633757)+1 种基金the Primary Research&Development Plan of Jiangsu Province(BE2017616,BE20187540,BE2019762,BE2020729)the Jiangsu Province Postdoctoral Science Foundation Funded Project(2019K185).
文摘To analyze and optimize the weapon system of systems(WSOS)scheduling process,a new method based on robust capabilities for WSOS scheduling optimization is proposed.First,we present an activity network to represent the military mission.The member systems need to be reasonably assigned to perform different activities in the mission.Then we express the problem as a set partitioning formulation with novel columns(activity flows).A heuristic branch-and-price algorithm is designed based on the model of the WSOS scheduling problem(WSOSSP).The algorithm uses the shortest resource-constrained path planning to generate robust activity flows that meet the capability requirements.Finally,we discuss this method in several test cases.The results show that the solution can reduce the makespan of the mission remarkably.
基金supported by the National Natural Science Foundation of China(U14352186140340161273189)
文摘In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis, reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.
