Multi-objective inventory models of deteriorating items have been developed with vague and imprecise information about available storage area. Here, the objectives are (i) to maximize the profit, (ii) to minimize the wastage cost due to deterioration and (iii) to minimize the total production cost. These objectives are also fuzzy in nature. In these models, production rate is a decision variabl...

In this paper, a multi-objective constrained optimization model is proposed to improve interpretability of TSK fuzzy models. This approach allows a linguistic approximation of the fuzzy models. Three different multi-objective evolutionary algorithms (MONEA, ENORA and NSGA-II) are used together with neural network techniques. These algorithms are checked out in the approximation of a dynamic non...

Recently fuzzy interval flexible linear programs have attracted many interests. These models are an extension of the classical programming which deal with crisp parameters. However, in most real-world applications, nature parameters decision-making problems is generally imprecise. Such uncertainties can lead to increased complexities related optimisation efforts. Simply ignoring these considere...

in this paper, we study the finitely many constraints of fuzzy relation inequalities problem and optimize the linear objective function on this region which is defined with fuzzy max-lukasiewicz operator. in fact lukasiewicz t-norm is one of the four basic t-norms. a new simplification technique is given to accelerate the resolution of the problem by removing the components having no effect on ...

in this paper, we study the finitely many constraints of the fuzzyrelation inequality problem and optimize the linear objectivefunction on the region defined by the fuzzy max-product operator.simplification operations have been given to accelerate theresolution of the problem by removing the components having noeffect on the solution process. also, an algorithm and somenumerical and applied exa...