This paper is comprised of the modeling and optimization of a multi objective linear programming problem in fuzzy environment in which some goals are fractional and some are linear. Here, we present a new approach for...This paper is comprised of the modeling and optimization of a multi objective linear programming problem in fuzzy environment in which some goals are fractional and some are linear. Here, we present a new approach for its solution by using α-cut of fuzzy numbers. In this proposed method, we first define membership function for goals by introducing non-deviational variables for each of objective functions with effective use of α-cut intervals to deal with uncertain parameters being represented by fuzzy numbers. In the optimization process the under deviational variables are minimized for finding a most satisfactory solution. The developed method has also been implemented on a problem for illustration and comparison.展开更多
Many kinds of uncertainties are involved, such as random, fuzzy, grey, unascertained property and so on, in soil erosion process. To exactly predict the non-point source pollution loads, some uncertainties should be t...Many kinds of uncertainties are involved, such as random, fuzzy, grey, unascertained property and so on, in soil erosion process. To exactly predict the non-point source pollution loads, some uncertainties should be taken into consideration. Aiming at the deficiency of present blind number theory being helpless for fuzziness, a novel blind number, i.e. extended-blind number, was introduced by substituting a set of triangular fuzzy numbers （TFNs）, expressed as a-cuts, for interval values in present blind number, and the expected value of extended-blind number was also brought forward by referring to the current blind number theory. On the basis of denoting the parameters of Uni- versal Soil Loss Equation （USLE） as extended-blind parameters, a novel USLE model was established for quantitatively evaluating soil erosion loss and non-point source pollution loads. As a case, the uncertain USLE was employed for predicting the soil erosion loss and non-point source pollution loads of absorbed nitrogen and phosphorus in a dis- trict in the Hangbu-Fengle River basin, in the upstream of Chaohu Lake watershed. The results show that it is feasible in theory to extend blind number into fuzzy environment and reliable on conclusion to apply extended-blind number theory for predicting non-point source pollution loads.展开更多
文摘This paper is comprised of the modeling and optimization of a multi objective linear programming problem in fuzzy environment in which some goals are fractional and some are linear. Here, we present a new approach for its solution by using α-cut of fuzzy numbers. In this proposed method, we first define membership function for goals by introducing non-deviational variables for each of objective functions with effective use of α-cut intervals to deal with uncertain parameters being represented by fuzzy numbers. In the optimization process the under deviational variables are minimized for finding a most satisfactory solution. The developed method has also been implemented on a problem for illustration and comparison.
基金Under the auspices of Tackling Key Program for Science and Technology of Anhui Province (No. 07010302165)Natural Science Foundation of Anhui Province (No. 050450303)
文摘Many kinds of uncertainties are involved, such as random, fuzzy, grey, unascertained property and so on, in soil erosion process. To exactly predict the non-point source pollution loads, some uncertainties should be taken into consideration. Aiming at the deficiency of present blind number theory being helpless for fuzziness, a novel blind number, i.e. extended-blind number, was introduced by substituting a set of triangular fuzzy numbers （TFNs）, expressed as a-cuts, for interval values in present blind number, and the expected value of extended-blind number was also brought forward by referring to the current blind number theory. On the basis of denoting the parameters of Uni- versal Soil Loss Equation （USLE） as extended-blind parameters, a novel USLE model was established for quantitatively evaluating soil erosion loss and non-point source pollution loads. As a case, the uncertain USLE was employed for predicting the soil erosion loss and non-point source pollution loads of absorbed nitrogen and phosphorus in a dis- trict in the Hangbu-Fengle River basin, in the upstream of Chaohu Lake watershed. The results show that it is feasible in theory to extend blind number into fuzzy environment and reliable on conclusion to apply extended-blind number theory for predicting non-point source pollution loads.
