In this paper a wide class of discrete optimization problems, which can be formulated as a 0-1 linear programming problem is discussed. It is assumed that the objective function costs are not precisely known. This uncertainty is modeled by specifying a finite set of fuzzy scenarios. Under every fuzzy scenario the costs are given as fuzzy intervals. Possibility theory is then applied to chose a ...

Many engineering optimization problems can be considered as linear programming problems where all or some of the parameters involved are linguistic in nature. These can only be quantified using fuzzy sets. The aim of this paper is to solve a fuzzy linear programming problem in which the parameters involved are fuzzy quantities with logistic membership functions. To explore the applicability of ...

The design of metamaterials is currently a fertile research domain. However, most of the metamaterial designs described in the literature arise from physical intuition, and often assume infinite periodicity. There is therefore a need for a design methodology capable of computing patterns and designs involving two different materials where the underlying design variables correspond to a finite s...

Modeling and solving real world problems is one of the most important issues in optimization problems. In this paper, we present an approach to solve Fuzzy Interval Flexible Linear Programming (FIFLP) problems that simultaneously have the interval ambiguity in the matrix of coefficients .In the first step, using the interval problem solving techniques; we transform the fuzzy interval flexible p...

Two advanced controllers were developed in this paper, i.e., a type-1 and a type-2 fuzzy logic controller and their performances compared in simulation for a case study, i.e., a binary distillation column, which is characterized by high nonlinearities and parameter uncertainties in the underlying mathematical model. Priority was given to the type-2 fuzzy controller, with special attention to in...

project planning is part of project management, which is relates to the use of schedules such as gantt charts to plan and subsequently report progress within the project environment. initially, the project scope is defined and the appropriate methods for completing the project are determined. in this paper a new approach for the critical path analyzing a project network with random fuzzy activi...

This paper presents a fuzzy goal programming (GP) procedure for solving a multiobjective linear plus linear fractional programming problem. In the proposed approach GP model for achievement of the highest membership value of each of fuzzy goal defined for the linear plus linear fractional objectives is formulated. In the solution process, the method of variable change on the underand overdeviat...

Nowadays fuzzy logic is increasingly used in decision-aided systems since it offers several advantages over other traditional decision-making techniques. The fuzzy decision support systems can easily deal with incomplete and/or imprecise knowledge applied to either linear or nonlinear problems. This paper presents the implementation of a combination of a Real/Binary-Like coded Genetic Algorithm...

This paper studies a facility location model with fuzzy random parameters and its swarm intelligence approach. A Value-at-Risk (VaR) based fuzzy random facility location model (VaR-FRFLM) is built in which both the costs and demands are assumed to be fuzzy random variables, and the capacity of each facility is unfixed but a decision variable assuming continuous values. Under this setting, the V...

− A new trend in the design of fuzzy rulebased systems is the use of evolutionary multiobjective optimization (EMO) algorithms. This trend is observed in various areas in machine learning. EMO algorithms are often used to search for a number of Pareto-optimal non-linear systems with respect to their accuracy and complexity. In this paper, we first explain some basic concepts in multiobjective o...