a procedure is presented that synthesizes fractional crystallization separation processes to obtain pure solids from multi-component solutions. the method includes a procedure to generate a network flow model to identify alternative process designs for fractional crystallization. the main advantage of this systematic procedure with respect to other reported procedures is using non-equilibrium s...

many ranking methods have been proposed so far. however, there is yet no method that can always give a satisfactory solution to every situation; some are counterintuitive, not discriminating; some use only the local information of fuzzy values; some produce different ranking for the same situation. for overcoming the above problems, we propose a new method for ranking fuzzy quantities based on ...

abstract a quantitative framework of combination of liner programming and cooperative game theory was used in this study to analyze and model cooperative contracts in production based on rural households' resources cooperation in firoozabad plain. revenues and costs in cooperation game theory have important rule to get agreement. transaction cost function was used in cooperative costs accountin...

Recently, Gasimov and Yenilmez proposed an approach for solving two kinds of fuzzy linear programming (FLP) problems. Through the approach, each FLP problem is first defuzzified into an equivalent crisp problem which is non-linear and even non-convex. Then, the crisp problem is solved by the use of the modified subgradient method. In this paper we will have another look at the earlier defuzzifi...

this paper uses the l1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (wdsnd) vectorsof a multi-objective mixed integer linear programming (momilp) problem.the proposed method generalizes the proposed approach by tohidi and razavyan[tohidi g., s. razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of...

‎Linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints‎. ‎In this paper‎, ‎to solve this problem‎, ‎we combine a discretization method and a neural network method‎. ‎By a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem‎. ‎Then‎, ‎we use...