Managers have begun to recognize that effectively managing risks in their business operations plays an important role in successfully managing their inventories. Accordingly, we develop a ðQ ; rÞ model based on fuzzy-set representations of various sources of uncertainty in the supply chain. Sources of risk and uncertainty in our model include demand, lead time, supplier yield, and penalty cost....

Assignment problem (AP) is a well known topic and is used very often in solving problems of engineering and management science. In this problem aij denotes the cost for assigning the jth job to the ith person. The cost is usually deterministic in nature. In this paper ãij has been considered to be trapezoidal and triangular numbers denoted by ãij which are more realistic and general in nature. ...

This paper proposes a comprehensive, multi-objective, mixed-integer, nonlinear programming (MINLP) model for a cell formation problem (CFP) under fuzzy and dynamic conditions aiming at: (1) minimizing the total cost which consists of the costs of intercellular movements and subcontracting parts as well as the cost of purchasing, operation, maintenance and reconfiguration of machines, (2) maximi...

This paper deals with fuzzy quantities and relations in multi-objective minimum cost flow problem. When t-norms and t-conorms are available, the goal programming is applied tominimize the deviation among themultiple costs of fuzzy flows and the given targets when the fuzzy supplies and demands are satisfied. To obtain the most optimistic and the most pessimistic satisficing solutions of this pr...

Several useful models have been developed by the software engineering community to elucidate the periodic growth of life cycle and calculate the effort of cost estimation in a precise manner. One of the commonly used machine learning techniques is the analogy method that cannot handle the categorical variables efficiently. In general, project attributes of cost estimation are often measured in ...

Recently, new applications have emerged that require database management systems with uncertainty capabilities. Many of the existing approaches to modelling uncertainty in database management systems are based on the theory of fuzzy sets. High performance is a necessary precondition for the acceptance of such systems by end users. However, performance issues have been quite neglected in researc...

In this paper, we propose a novel fuzzy-based framework for routing and wavelength assignment in alloptical DWDM backbone networks with sparse wavelength conversion capabilities. While most of the previous work in this field focuses on optical networks without wavelength conversion with full wavelength conversion capabilities, in this work we study networks with sparse wavelength conversion res...

This paper presents a sum of squares (SOS) approach to guaranteed cost control of polynomial discrete fuzzy systems. First, we present a polynomial discrete fuzzy model that is more general representation of the well-known discrete Takagi-Sugeno (T-S) fuzzy model. Secondly, we derive a design condition based on polynomial Lyapunov functions that contain quadratic Lyapunov functions as a special...

In this paper, we introduce a robust state feedback controller design using Linear Matrix Inequalities (LMIs) and guaranteed cost approach for Takagi-Sugeno fuzzy systems. The purpose on this work is to establish a systematic method to design controllers for a class of uncertain linear and non linear systems. Our approach utilizes a certain type of fuzzy systems that are based on Takagi-Sugeno ...

Monte Carlo simulation has been used extensively for addressing probabilistic uncertainty in range estimating for construction projects. However, subjective and linguistically expressed information results in added non-probabilistic uncertainty in construction management. Fuzzy logic has been used successfully for representing such uncertainties in construction projects. In practice, an approac...