This work develops an interactive fuzzy multi-objective linear programming (i-FMOLP) method for solving the fuzzy multiobjective transportation problems with piecewise linear membership function. The proposed i-FMOLP method aims to simultaneously minimize the total distribution costs and the total delivery time with reference to fuzzy available supply and total budget at each source, and fuzzy ...

This paper introduces an optimal fuzzy proportional–integral–derivative (PID) controller. The fuzzy PID controller is a discrete-time version of the conventional PID controller, which preserves the same linear structure of the proportional, integral, and derivative parts but has constant coefficient yet self-tuned control gains. Fuzzy logic is employed only for the design; the resulting control...

Paknejad et al.’s model is considered in this paper. Itemwise multiobjective models for both exponential and uniform lead-time demand are taken and the results are compared numerically both in fuzzy optimization and intuitionistic fuzzy optimization techniques. Objective of this paper is to establish that intuitionistic fuzzy optimizaion method is better than usual fuzzy optimization technique ...

This paper discusses the linguistic knowledge extraction from the iterative execution of a multiplayer non-cooperative repeated game. Linguistic knowledge is automatically extracted in the form of fuzzy if-then rules. Our knowledge extraction is mainly based on the on-line incremental learning of fuzzy rule-based systems. In this sense, our linguistic knowledge extraction is the learning of fuz...

The purpose of the paper is to study how to solve a type of matrix games with payoffs of triangular fuzzy numbers. In this paper, the value of a matrix game with payoffs of triangular fuzzy numbers has been considered as a variable of the triangular fuzzy number. First, based on two auxiliary linear programming models of a classical matrix game and the operations of triangular fuzzy numbers, fu...

This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the EED as a true multiobjective optimization problem with competing and noncommensurable obj...

This paper presents a new approach to multiobjective optimization by evolutionary algorithm. The approach is based on fuzzification of Pareto dominance relation. Using fuzzy degrees of dominance, a set of vectors (multiple objectives) can be partially ranked. The FDD algorithm, a modification of standard genetic algorithm using this ranking scheme for the selection operations, is presented and ...

The paper introduces a novel problem based on causal modeling in marketing where knowledge discovery is able to provide useful results (as shown in a real-world application). The problem features (with uncertain data and available expert knowledge) and the proposed multiobjective optimization approach makes genetic fuzzy systems to be a good framework to deal with that.

A fuzzy logic based expert system has been developed that automatically allocates resources in realtime over many dissimilar platforms. The platforms can be very general, e.g., ships, planes, etc. Potential foes can also be general. The resource manager has been embedded in an electronic game environment. This coevolutionary game fully automates the data mining problem allowing determination of...

System reliability optimization is often faced with imprecise and conflicting goals such as reducing the cost of the system and improving the reliability of the system. The decision making process becomes fuzzy and multi-objective. In this paper, we formulate the problem as a fuzzy multi-objective nonlinear program (FMOOP). A fuzzy multiobjective genetic algorithm approach (FMGA) is proposed fo...