Evaluation of suspended load transport rate using transport formulas and artificial neural network models （Case study： Chelchay Catchment）＊

Accurate estimation of sediment load or transport rate is very important to a wide range of water resources projects. This study was undertaken to determine the most appropriate model to predict suspended load in the Chelchay Watershed, northeast of Iran. In total, 59 data series were collected from four gravel bed-rivers and a sand bed river and two depth integrating suspended load samplers to evaluate nine suspended load formulas and feed forward backpropagation Artificial Neural Network (ANN) structures. Although the Chang formula with higher correlation coefficient (r = 0.69) and lower Root Mean Square Error (RMSE = 0.013) is the best suspended load predictor among the nine studied formulas, the ANN models significantly outperform traditional suspended load formulas and show their superior performance for all statistical parameters. Among different ANN structures two models including 4 inputs, 4 hidden and one output neurons, and 4 inputs, 4 and one hidden and one output neurons provide the best simulation with the RMSE values of 0.0009 and 0.001, respectively.     

Multi-product multi-chance-constraint stochastic inventory control problem with dynamic demand and partial back-ordering: A harmony search algorithm

In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the end, three numerical examples of different sizes are given to demonstrate the applicability of the proposed methodology in real world inventory control problems, to validate the results obtained, and to compare its performances with the ones of both a genetic and a particle swarm optimization algorithms.     

Optimum loading of machines in a flexible manufacturing system using a mixed-integer linear mathematical programming model and genetic algorithm

Machine loading problem in a flexible manufacturing system (FMS) encompasses various types of flexibility aspects pertaining to part selection and operation assignments. The evolution of flexible manufacturing systems offers great potential for increasing flexibility by ensuring both cost-effectiveness and customized manufacturing at the same time. This paper proposes a linear mathematical programming model with both continuous and zero-one variables for job selection and operation allocation problems in an FMS to maximize profitability and utilization of system. The proposed model assigns operations to different machines considering capacity of machines, batch-sizes, processing time of operations, machine costs, tool requirements, and capacity of tool magazine. A genetic algorithm (GA) is then proposed to solve the formulated problem. Performance of the proposed GA is evaluated based on some benchmark problems adopted from the literature. A statistical test is conducted which implies that the proposed algorithm is robust in finding near-optimal solutions. Comparison of the results with those published in the literature indicates supremacy of the solutions obtained by the proposed algorithm for attempted model.     

Optimal pricing, lot-sizing and marketing planning in a capacitated and imperfect production system

In the classical economic production quantity (EPQ) problem demand is considered to be known in advance. However, in the real-world, demand of a product is a function of factors such as product’s price, its quality, and marketing expenditures for promoting the product. Quality level of the product and specifications of the adopted manufacturing process also affect the unit product’s cost. Therefore, in this paper we consider a profit maximizing firm who wants to jointly determine the optimal lot-sizing, pricing, and marketing decisions along with manufacturing requirements in terms of flexibility and reliability of the process. Geometric programming (GP) technique is proposed to address the resulting nonlinear optimization problem. Using recent advances in optimization techniques we are able to optimally solve the developed, highly nonlinear, mathematical model. Finally, using numerical examples, we illustrate the solution approach and analyze the solution under different conditions.     

Genetic application in a facility location problem with random demand within queuing framework

In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand and immobile servers is studied. Two objectives considered in this problem are: (1) minimizing the average customer waiting time and (2) minimizing the average facility idle-time percentage. We formulate this problem using queuing theory and solve the model by a genetic algorithm within the desirability function framework. Several examples are presented to demonstrate the applications of the proposed methodology.     

Classification of non-alcoholic beer based on aftertaste sensory evaluation by chemometric tools

Sensory evaluation is the application of knowledge and skills derived from several different scientific and technical disciplines, physiology, chemistry, mathematics and statistics, human behavior, and knowledge about product preparation practices. This research was aimed to evaluate aftertaste sensory attributes of commercial non-alcoholic beer brands (P1, P2, P3, P4, P5, P6, P7) by several chemometric tools. These attributes were bitter, sour, sweet, fruity, liquorice, artificial, body, intensity and duration. The results showed that the data are in a good consistency. Therefore, the brands were statistically classified in several categories. Linear techniques as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were performed over the data that revealed all types of beer are well separated except a partial overlapping between zones corresponding to P4, P6 and P7. In this research, for the confirmation of the groups observed in PCA and in order to calculate the errors in calibration and in validation, PLS-DA technique was used. Based on the quantitative data of PLS-DA, the classification accuracy values were ranked within 49-86%. Moreover, it was found that the classification accuracy of LDA was much better than PCA. It shows that this trained sensory panel can discriminate among the samples except an overlapping between two types of beer. Also, two types of artificial networks were used: Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Back Propagation (BP) learning method. The highest classification success rate (correct predicted number over total number of measurements) of about 97% was obtained for RBF followed by 94% for BP. The results obtained in this study could be used as a reference for electronic nose and electronic tongue in beer quality control.     

Reduction of Noise from Disc Brake Systems Using Composite Friction Materials Containing Thermoplastic Elastomers (TPEs)

Attempts have been made for the first time to prepare a friction material with the characteristic of thermal sensitive modulus, by the inclusion of thermoplastic elastomers (TPE) as viscoelastic polymeric materials into the formulation in order to the increase the damping behavior of the cured friction material. Styrene–butadiene–styrene (SBS), styrene–ethylene–butylene–styrene (SEBS) and nitrile rubber/polyvinyl chloride (NBR/PVC) blend system were used as TPE materials. In order to evaluate the viscoelastic parameters such as loss factor (tan δ) and storage modulus (E′) for the friction material, dynamic mechanical analyzer (DMA) were used. Natural frequencies and mode shapes of friction material and brake disc were determined by modal analysis. However, NBR/PVC and SEBS were found to be much more effective in damping behavior. The results from this comparative study suggest that the damping characteristics of commercial friction materials can be strongly affected by the TPE ingredients. This investigation also confirmed that the specimens with high TPE content had low noise propensity.     

Flow resistance in a compound gravel-bed bend

In this paper, the effect of a gravel-bed in a compound bend (similar to sinusoidal top view) of a natural river (Zayandehrud River flowing through Isfahan, Iran) has been investigated for flow resistance analysis, measuring the velocity with a micro current meter. The data were analysed and the following observations were made. In a compound bend, the law of the wall can be valid for up to 66% of the flow depth from the bed. The parabolic law is the most effective method for the determination of shear velocity. Based on the existing criteria for verifying the equilibrium boundary layer, the flow cannot be in equilibrium. The shear stress distribution and the sediment transport parameters have considerable influence on resistance to flow. Froude number and the flow depth relative to the representative gravel size have little effect on the flow resistance estimation.     

Parametric meshless Galerkin method

In meshless methods, generation of meshless shape functions is usually a complicated and time‐consuming task. In this paper, a new meshless method called parametric meshless Galerkin method (PMGM) is presented. In this method, meshless shape functions are constructed on meshless parametric domains (MPD), before running to solve the problem. For modelling the new problems, MPDs are mapped to the physical space. Therefore the shape functions constructing time can be saved. Mapping is simply performed by defining a linear function. Also, the integration grids are defined in the MPD and it is not necessary to create background integration grids separately for each problem. The method is described for two‐dimensional problems, but it can be applied to three‐dimensional problems in the same way. It is shown that using the PMGM, a time saving as much as 21% is achieved with respect to the element‐free Galerkin method for the numerical examples and the obtained results show efficiency and convergence of the method. Copyright © 2005 John Wiley & Sons, Ltd.