Research On The Evaluation Methodology Of Technology Contribution Degree To The Weapon System Of Systems

High military technology and military equipments have brought more and more important effect on the modern information war.In the meanwhile,the confrontation between Weapon System of Systems(WSo S)has become the main content of the modern information war.Therefore,the construction of WSo S has played an important role in the national defense and the armed forces.For the limitation of our resources,we have to choose part of the high military technologies to develop.And therefore,there is a pressing demand to evaluate the effect and influence of the new military technologies on the WSo S.Motivated by this practical problem,this paper does some research on the evaluation method of the Technology Contribution Degree to provide suggestions to the strategic decision makers.It can be found that the available literatures about the Technology Contribution Degree evaluation are mostly based on the simulation method.And there has been no evaluation methodology based on the analytical models.Therefore,this paper proposes an analytical evaluation methodology based on the Do DAF and Data Envelopment Analysis(DEA).First,Do DAF is used to build the architecture framework for the Technology Contribution Degree evaluation problem.Then the DEA model is used as the calculation model for this problem.Comparing with the existent methods,the methodology proposed in this paper has some advantages as follows: quantitative,non-parameterized and coincident between different levels.The influence data of the technology on the performance of the military equipments is the foundation of the evaluation of the Technology Contribution Degree.It is firstly supposed that the exact data is available during the Technology Contribution Degree evaluation in this paper.Then the cross-efficiency evaluation model is used as the calculation model with the following modification: first,this paper proposes an iterated model in DEA method with non-zero weights;second,the non-zero weights are used to calculate the cross-efficiency scores;finally,a modified TOPSIS method is used as the aggregation method of the cross-efficiency scores.Uncertainty is an important issue during the evaluation of Technology Contribution Degree.In this paper,the interval data is used to represent the uncertain information during the evaluation of Technology Contribution Degree.The cross-efficiency evaluation model is still used as the calculation model and the interval data has been introduced into the cross-efficiency evaluation method.Considering the drawbacks in the existent cross-efficiency models with interval data,this paper separately propose the upper bound model and the lower bound model of the cross-efficiency with interval data.What is more,a modified TOPSIS procedure is used to aggregate the interval cross-efficiency scores.As the research on the evaluation method of Technology Contribution Degree has been proposed,this paper also proposes some research on the sensitivity and stability analysis of the DEA-based model.The sensitivity and stability analysis means to analysis the effect of the variations of inputs and outputs data of Decision Making Units(DMUs)in the DEA model on their efficiency scores.For the efficient DMUs,the sensitivity and stability analysis is able to provide a sufficient condition for remaining their efficiency.For the inefficient DMUs,the sensitivity and stability analysis is able to provide some sufficient conditions for improving their efficiency.Some useful information can be got by the sensitivity and stability analysis in the Technology Contribution Degree evaluation.Another practical requirement in the Technology Contribution Degree evaluation is the combinatorial efficiency evaluation of the DEA method.The decision makers are usually required to choose a number of DMUs instead of a single one in the efficiency evaluation problem.This paper proposes a 0-1 Knapsack Problem formulation of the combinatorial efficiency evaluation and also proposes an improved combinatorial efficiency evaluation model based on the super efficiency model.The new model proposed in this paper is more effective in discriminating the efficiency of combinatorial DMUs.What is more,this paper also proposes a modified local search algorithm as a solver of the combinatorial optimization problem.