Unit commitment optimization for the scheduling of units and effective load sharing among thermal units is extensively used in electrical power system planning. The target of unit commitment optimization will be economical when the criteria is to test the best combination of thermal units to serve the load with the optimium load sharing among units satisfying various constraints like load deman...

In terms of flexibility and product variety in lot-sizing systems of crisp cases, the average demand of per unit of time (mj), the relative duration of setup (qj), and the unit cost of production (cj) are considered. Instead of using the usual method that the mj, qj, and cj in the total cost function are respectively fuzzified by the triangular fuzzy numbers to derive fuzzy total cost, in this ...

The accuracy of algorithmic models for software cost prediction is limited due to their inability to handle imprecision and uncertainties associated with the software project attributes like size, programmer experience, etc. This paper enhances the accuracy and sensitivity of one of a widely used models COCOMO81 intermediate by incorporating a fuzzy component into the model. The fuzzy component...

The aim of Fuzzy transportation is to find the least transportation cost of some commodities through a capacitated network when the supply and demand of nodes and the capacity and cost of edges are represented as fuzzy numbers. Many previous papers [4, 5, 13, 14] have presented arithmetic operations, alpha level and simple ranking by operations. P. Pandian [7, 8] has presented some methods for ...

A risk matrix is a mechanism to characterize and rank process risks that are typically identified through one or more multifunctional reviews (e.g., process hazard analysis, audits, or incident investigation). This paper describes a procedure for developing a fuzzy risk matrix that may be used for emerging fuzzy logic applications in different safety analyses (e.g., LOPA). The fuzzification of ...

The adaptive fuzzy and fuzzy neural models are being widely used for identification of dynamic systems. This paper describes different fuzzy logic and neural fuzzy models. The robustness of models has further been checked by Simulink implementation of the models with application to the problem of system identification. The approach is to identify the system by minimizing the cost function using...

Abstract This paper is concerned with observer-based guaranteed cost control design of fuzzy bilinear systems with time-varying delay. First, we consider the state feedback control design by assuming a special form of a fuzzy controller. A delay-dependent condition, which is less conservative than delay-independent one, for guaranteed cost control design of fuzzy bilinear systems with time-vary...

Applications of neural network were widely used in construct project cost estimate. Aim at handling weakness of poor convergence and insufficient forecast, an improved fuzzy neural network method based on SOFM (self-organizing feature map) was proposed to replace the fashionable T-S fuzzy neural network. The method illustrated how to apply SOFM to improve the fault such as poor convergence and ...

This paper deals with infinite time horizon fuzzy Economic Order Quantity (EOQ) models for deteriorating items with stock dependent demand rate and nonlinear holding costs by taking deterioration rate 0 θ as a triangular fuzzy number ( ) , , 2 0 0 1 0 δ θ θ δ θ + − , where 0 2 1 , 0 θ δ δ < < are fixed real numbers. The traditional parameters such as unit cost and ordering cost have been kept c...

Hybrid Electric Vehicles (HEVs) are driven by two energy convertors, i.e., an Internal Combustion (IC) engine and an electric machine. To make powertrain of HEV as efficient as possible, proper management of the energy elements is essential. This task is completed by HEV controller, which splits power between the IC engine and Electric Motor (EM). In this paper, a Genetic-Fuzzy control strategy...