8,186 research outputs found
An Interactive Fuzzy Satisficing Method for Fuzzy Random Multiobjective 0-1 Programming Problems through Probability Maximization Using Possibility
In this paper, we focus on multiobjective 0-1 programming problems under the situation where stochastic uncertainty and vagueness exist at the same time. We formulate them as
fuzzy random multiobjective 0-1 programming problems where coefficients of objective functions are fuzzy random variables. For the formulated problem, we propose an interactive fuzzy satisficing method through probability maximization using of possibility
Strict Solution Method for Linear Programming Problem with Ellipsoidal Distributions under Fuzziness
This paper considers a linear programming problem with ellipsoidal distributions including fuzziness. Since this problem is not well-defined due to randomness and fuzziness, it is hard to solve it directly. Therefore, introducing chance constraints, fuzzy goals and possibility measures, the proposed model is transformed into the deterministic equivalent problems. Furthermore, since it is difficult to solve the main problem analytically and efficiently due to nonlinear programming, the solution method is constructed introducing an appropriate parameter and performing the equivalent transformations
Fuzziness and Funds Allocation in Portfolio Optimization
Each individual investor is different, with different financial goals,
different levels of risk tolerance and different personal preferences. From the
point of view of investment management, these characteristics are often defined
as objectives and constraints. Objectives can be the type of return being
sought, while constraints include factors such as time horizon, how liquid the
investor is, any personal tax situation and how risk is handled. It's really a
balancing act between risk and return with each investor having unique
requirements, as well as a unique financial outlook - essentially a constrained
utility maximization objective. To analyze how well a customer fits into a
particular investor class, one investment house has even designed a structured
questionnaire with about two-dozen questions that each has to be answered with
values from 1 to 5. The questions range from personal background (age, marital
state, number of children, job type, education type, etc.) to what the customer
expects from an investment (capital protection, tax shelter, liquid assets,
etc.). A fuzzy logic system has been designed for the evaluation of the answers
to the above questions. We have investigated the notion of fuzziness with
respect to funds allocation.Comment: 21 page
Interactive Fuzzy Programming for Stochastic Two-level Linear Programming Problems through Probability Maximization
This paper considers stochastic two-level linear programming problems. Using the concept of chance constraints and probability maximization, original problems are transformed into deterministic ones. An interactive fuzzy programming method is presented for deriving a satisfactory solution efficiently with considerations of overall satisfactory balance
Emergency response network design for hazardous materials transportation with uncertain demand
Transportation of hazardous materials play an essential role on keeping a friendly environment. Every day, a substantial amount of hazardous materials (hazmats), such as flammable liquids and poisonous gases, need to be transferred prior to consumption or disposal. Such transportation may result in unsuitable events for people and environment. Emergency response network is designed for this reason where specialist responding teams resolve any issue as quickly as possible. This study proposes a new multi-objective model to locate emergency response centers for transporting the hazardous materials. Since many real-world applications are faced with uncertainty in input parameters, the proposed model of this paper also assumes that reference and demand to such centre is subject to uncertainty, where demand is fuzzy random. The resulted problem formulation is modelled as nonlinear non-convex mixed integer programming and we used NSGAII method to solve the resulted problem. The performance of the proposed model is examined with several examples using various probability distribution and they are compared with the performance of other existing method
Order-of-Magnitude Influence Diagrams
In this paper, we develop a qualitative theory of influence diagrams that can
be used to model and solve sequential decision making tasks when only
qualitative (or imprecise) information is available. Our approach is based on
an order-of-magnitude approximation of both probabilities and utilities and
allows for specifying partially ordered preferences via sets of utility values.
We also propose a dedicated variable elimination algorithm that can be applied
for solving order-of-magnitude influence diagrams
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