This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly know...This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.展开更多
A short-time scaling criterion of variable ordering of OBDDs is proposed. By this criterion it is easy and fast to determine which one is better when several. variable orders are given, especially when they differ 10%...A short-time scaling criterion of variable ordering of OBDDs is proposed. By this criterion it is easy and fast to determine which one is better when several. variable orders are given, especially when they differ 10% or more in resulted BDD size from each other. An adaptive variable order selection method, based on the short-time scaling criterion, is also presented. The experimental results show that this method is efficient and it makes the heuristic variable ordering methods more practical.展开更多
An enhanced ordered binary decision diagram （EOBDD） algorithm is proposed to evaluate the reliability of wireless sensor networks （WSNs）, based on the considerations of the common cause failure （CCF） and a large...An enhanced ordered binary decision diagram （EOBDD） algorithm is proposed to evaluate the reliability of wireless sensor networks （WSNs）, based on the considerations of the common cause failure （CCF） and a large number of nodes in WSNs. The EOBDD algorithm analyzes the common cause event （CCE） and the network structure when CCE takes place according to the stochastic graph and the CCF model of WSNs. After constructing the ordered binary decision diagram （OBDD） of the original network with node expansion, it uses a set of OBDD variables （SOV） to guide reliability computations along this OBDD. The two steps about OBDD can decrease the cost of OBDD constructions and storage. Furthermore, the efficient OBDD structure and Hash tables can greatly decrease redundant computations of isomorphs. The experiment results show that the EOBDD can be used to evaluate the reliability of WSN efficiently.展开更多
基金supported by the National Natural Science Foundation of China (70473037)the Key Project of National Development and Reform Commission (1009-213011)
文摘This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.
文摘A short-time scaling criterion of variable ordering of OBDDs is proposed. By this criterion it is easy and fast to determine which one is better when several. variable orders are given, especially when they differ 10% or more in resulted BDD size from each other. An adaptive variable order selection method, based on the short-time scaling criterion, is also presented. The experimental results show that this method is efficient and it makes the heuristic variable ordering methods more practical.
基金supported by the National Natural Science Foundation of China (60672086)the Hi-Tech Research and Development Program of China (2007AA01Z2A1, 2008AA01A316)the EUFPT Project EFIPSANS (215547), and the Foundation for Western Returned Chinese Scholars of the Ministry of Education
文摘An enhanced ordered binary decision diagram （EOBDD） algorithm is proposed to evaluate the reliability of wireless sensor networks （WSNs）, based on the considerations of the common cause failure （CCF） and a large number of nodes in WSNs. The EOBDD algorithm analyzes the common cause event （CCE） and the network structure when CCE takes place according to the stochastic graph and the CCF model of WSNs. After constructing the ordered binary decision diagram （OBDD） of the original network with node expansion, it uses a set of OBDD variables （SOV） to guide reliability computations along this OBDD. The two steps about OBDD can decrease the cost of OBDD constructions and storage. Furthermore, the efficient OBDD structure and Hash tables can greatly decrease redundant computations of isomorphs. The experiment results show that the EOBDD can be used to evaluate the reliability of WSN efficiently.
