A method for incorporating fuzzy preferences into evolutionary multiobjective optimization is proposed. After introducing three commonly used models for describing fuzzy preferences, a method to convert fuzzy preferences into realvalued weight intervals is suggested. It is argued that to convert fuzzy preferences into interval-based weights is more consistent with the motivation of using fuzzy ...

We present the framework of multiobjective fractional transportation problem in form pentagonal fuzzy supply and demand. The ideal model is set up to match decision makers’ preferences competing for criteria, costs, delivery time, degradation, environmental social concerns are objectives. employed flexible goal programming handle Model’s complexity improve reasonable compromise. real-world wind...

In this paper, a stochastic multiobjective framework is proposed for a day-ahead short-term Hydro Thermal Self-Scheduling (HTSS) problem for joint energy and reserve markets. An efficient linear formulations are introduced in this paper to deal with the nonlinearity of original problem due to the dynamic ramp rate limits, prohibited operating zones, operating services of thermal plants, multi-h...

In this paper, we study measurement of sensitivity for changes of violations in the aspiration level for the fuzzy multiobjective linear fractional programming problem. c © 2001 Elsevier Science B.V. All rights reserved.

This article describes a multiobjective spatial fuzzy clustering algorithm for image segmentation. To obtain satisfactory segmentation performance for noisy images, the proposed method introduces the non-local spatial information derived from the image into fitness functions which respectively consider the global fuzzy compactness and fuzzy separation among the clusters. After producing the set...

Artificial neural networks are massively paralleled distributed computation and fast convergence and can be considered as an efficient method to solve real-time optimization problems. In this paper, we propose reference point based neural network algorithm for solving fuzzy multiobjective optimization problems MOOP. The target is to identify the Pareto-optimal region closest to the reference po...

A novel supply chain operational transport planning model is developed in this paper. The goals of the model are to minimize the number of used trucks and the total inventory levels. Because of somewhat imprecise nature of vehicle capacities and decision makers’ aspiration levels for the goals, a fuzzy multiobjective linear programming (FMOLP) modeling approach is adopted. Moreover, an interact...

This paper develops a fuzzy multi-objective linear programming (FMOLP) model for solving a multiobjective single-machine scheduling problem. The proposed model attempts to minimize the total weighted tardiness andmakespan simultaneously. In this problem, a proposed FMOLPmethod is applied with respect to the overall acceptable degree of thedecisionmaker (DM) satisfaction. Anumber of numerical ex...