fuzzy linear programming models and methods has been one ofthe most and well studied topics inside the broad area of soft computing. itsapplications as well as practical realizations can be found in all the real worldareas. in this paper a basic introduction to the main models and methods infuzzy mathematical programming, with special emphasis on those developedby the authors, is presented. as ...

Recently, fuzzy linear programming problems have been considered by many. In the literature of fuzzy linear programming several models are offered and therefore some various methods have been suggested to solve these problems. One of the most important of these problems that recently has been considered; are Fully Fuzzy Linear Programming (FFLP), which all coefficients and variables of the prob...

DEA (Data Envelopment Analysis) is a technique for evaluating the relative effectiveness of decision-making units (DMU) with multiple inputs and outputs data based on non-parametric modeling using mathematical programming (including linear programming, multi-parameter programming, stochastic programming, etc.). The classical DEA methods are developed to handle the information in the form of cri...

We propose a novel concurrent programming framework called ACL. ACL is a variant of linear logic programming, where computation is described in terms of bottom-up proof search of some formula in linear logic. The whole linear sequent calculus is too non-deterministic to be interpreted as an operational semantics for a realistic programming language. We restrict formulas and accordingly rene inf...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

cost reduction is one of the methods applied for improving the productivity of organizations. in productivity literature, particularly in nonparametric methods, cost reduction related methods are regarded as input oriented models. this paper presents a supply chain management (scm) model in which purchasing iron ore and coke from different resources, along with production and distribution of st...

this paper presents a genetic algorithm (ga) for solving a generalized model of single-item resource-constrained aggregate production planning (app) with linear cost functions. app belongs to a class of pro-duction planning problems in which there is a single production variable representing the total production of all products. we linearize a linear mixed-integer model of app subject to hiring...

this paper is focused on the tactical design of steel supply chain (ssc). a general mathematical model is proposed to integrate production and transportation planning in multi-commodity ssc. the main purpose is to prepare a countrywide production and distribution plan in an ssc with three layers consisting of iron ore mines as suppliers, steel companies as producers, and subsidiary steel compan...

information on the productivity, costs and applications of the logging system is a key component in the evaluation of management plans for the rehabilitation and utilization of caspian forests. skidding and road construction costs are expensive forest operations. determining the optimum forest road network density is one of the most important factors in sustainable forest management. logging me...