This paper proposes probabilistic default reasoning as a suitable approach to inheritance and recognition in uncertain and fuzzy object-oriented models. Firstly, we introduce an uncertain and fuzzy object-oriented model where a class property (i.e., an attribute or a method) can contain fuzzy sets interpreted as families of probability distributions, and uncertain class membership and property ...

Uncertainty theory is a mathematical methodology for dealing withnon-determinate phenomena in nature. As we all know, uncertainprocess and uncertain integral are important contents of uncertaintytheory, so it is necessary to have deep research. This paperpresents the definition and discusses some properties of strongcomonotonic uncertain process. Besides, some useful formulas ofuncertain integr...

This paper presents a semidefinite relaxation technique for computing a minimal bounding ellipsoid that contains the set of static responses of an uncertain truss. We assume that both member stiffnesses and external forces are uncertain but bounded. By using a combination of the quadratic embedding technique of the uncertainty and the Sprocedure, we formulate a semidefinite programming (SDP) pr...

This paper mainly investigates the location problem of multi-product logistics distribution centers in uncertain environment. Based on the assumption that the customers’ demands and the transportation times are uncertain variables, an uncertain programming model is constructed. On the precondition of satisfying the capacity constraint and time window constraint, the objective of the model is to...

Generally, it is very difficult to determine the medicine supply in hospital under uncertain environment. Here, the medical supply decision problem in uncertain environment is modeled as a fuzzy multi-objective linear programming model. First, the medicine supply in hospital management system is analyzed and the uncertainties in medicine supply are modeled as fuzzy numbers. Second, a fuzzy medi...

This work introduces a robust formulation of the uncertain set covering problem combining the concepts of robust and probabilistic optimization and defines ’Γ-robust α-covers’. It is shown that the proposed robust uncertain set covering problem can be stated as a compact mixed-integer linear programming model which can be solved with modern computer software. This model is a natural extension o...

Present paper is an application study of intuitionistic fuzzy optimization technique in agricultural production planning problem particularly a case of smallholder farmer in north Bihar, India. Generally, the crop planning problem is formulated as linear programming problems. but in realistic situation there are many uncertain factors in agricultural production planning problems and hence futur...

Although we usually would like to work with exact systems, most of the real world systems are nonlinear with uncertain parameters. In this paper, we propose AVK (A.V. Kamyad) approach to solve nonlinear problems with uncertain parameters (NPUP). This approach substitutes the original nonlinear system with an equivalent nonlinear programming (NLP) problem. Using this approach, we found an optima...

We introduce strong formulations for robust mixed 0–1 programming with uncertain objective coefficients. We focus on a polytopic uncertainty set described by a “budget constraint” for allowed uncertainty in the objective coefficients. We show that for a robust 0–1 problem, there is an α–tight linear programming formulation with size polynomial in the size of an α–tight linear programming formul...

This paper discusses the optimization of emergency resource scheduling for major railway emergencies under multiple uncertainties while considering in demand, reserve, and transportation costs resources. We introduce a novel approach that integrates stochastic mathematical programming, interval parameter fuzzy programming to study uncertain interactions coupling. A two-stage credibility-constra...