A fuzzy MCDM approach for stock selection

A fuzzy MCDM approach is applied to the stock selection problem, where the proposed approach can deal with qualitative information in addition to quantitative information. A hierarchy of major–sub criteria is then established to reduce the dependence between criteria. The ratings of alternatives versus qualitative sub-criteria and the weights of major- and sub-criteria are assessed in linguistic terms represented by fuzzy numbers. Each sub-criterion is in a benefit, cost, or balanced nature. New standardization methods for fuzzy numbers in the cost and balanced nature are presented. The algorithms of membership functions of the final aggregation are completely developed instead of approximation. The final aggregations in fuzzy numbers are then defuzzified to crisp values in order to rank the performance of alternatives. Moreover, the ratio of market price to performance (PP) is suggested to filter the over/under-pricing of alternatives. A set of buying/selling strategies are recommended according to the performance and PP. An empirical example then demonstrates the processing of the proposed approach.     

A QFD-based fuzzy MCDM approach for supplier selection

Supplier selection is a highly important multi-criteria group decision making problem, which requires a trade-off between multiple criteria exhibiting vagueness and imprecision with the involvement of a group of experts. In this paper, a fuzzy multi-criteria group decision making approach that makes use of the quality function deployment (QFD) concept is developed for supplier selection process. The proposed methodology initially identifies the features that the purchased product should possess in order to satisfy the company’s needs, and then it seeks to establish the relevant supplier assessment criteria. Moreover, the proposed algorithm enables to consider the impacts of inner dependence among supplier assessment criteria. The upper and the lower bounds of the weights of supplier assessment criteria and ratings of suppliers are computed by using the fuzzy weighted average (FWA) method. The FWA method allows for the fusion of imprecise and subjective information expressed as linguistic variables or fuzzy numbers. The method produces less imprecise and more realistic overall desirability levels, and thus it rectifies the problem of loss of information. A fuzzy number ranking method that is based on area measurement is used to obtain the final ranking of suppliers. The computational procedure of the proposed framework is illustrated through a supplier selection problem reported in an earlier study.     

A fuzzy attractiveness of market entry (FAME) model for market selection decisions

A Fuzzy Attractiveness of Market Entry (FAME) model is developed to address the decision-making problem of product introduction into alternative markets. FAME is a market entry selection model that is specifically designed to handle situations when information is limited and/or ambiguous, and a high level of uncertainty exists. As such, the FAME model is an easy to implement tool that supports a reasoning approach to market selection decisions. The model uses expert opinions regarding four factors: (1) fit of the firm's marketing mix in each market; (2) the fit of its key competitor's marketing mix in each market; (3) environmental conditions in each market; and (4) the strategic importance of each market to the firm. Application of the model algorithm is conducted for a small, Bulgarian winery's market selection decision. Ease of use is relevant for small to mid-size companies since a spreadsheet is sufficient to complete the algorithmic calculations.     

An adaptively managed dynamic portfolio selection model using a time-varying investment target according to the market forecast

In this paper, we propose an adaptive investment strategy (AIS) based on a dynamic portfolio selection model (DPSM) that uses a time-varying investment target according to the market forecast. The DPSM allows for flexible investments, setting relatively aggressive investment targets when market growth is expected and relatively conservative targets when the market is expected to be less attractive. The model further allows investments to be liquidated into risk-free assets when the market forecast is pessimistic. By dynamically determining the investment target, the DPSM allows construction of portfolios that are more responsive to market changes, while eliminating the possibility of the model becoming infeasible under certain market conditions. When the proposed DPSM is implemented in real-life investment scenarios using the AIS, the portfolio is rebalanced according to a predefined rebalancing cycle and the model’s input parameters are estimated on each rebalancing date using an exponentially weighted moving average (EWMA) estimator. To evaluate the performance of the proposed approach, a 7-year investment experiment was conducted using historical stock returns data from 10 different stock markets around the world. Performance was assessed and compared using diverse measures. Superior performance was achieved using the AIS proposed herein compared with various benchmark approaches for all performance measures. In addition, we identified a converse relationship between the average trading volume of a market and the value of the weighting parameter prescribed to the EWMA estimator, which maximizes cumulative returns in each market.     

An inexact-stochastic dual water supply programming model

This paper introduces an inexact-stochastic dual water supply programming (ISDWSP) model based on analysis of the inexact characteristics in demand and supply subsystems of dual water supply system and their dynamic interactions. The model is based on an inexact chance-constrained programming (ICCP) method allowing both distribution information in B (right parameter in the model constrain) and uncertainties in A (left parameter in the model constrain) and C (parameter in the model function) with objective of maximizing economic return, and constrained to available water resource, economical, environmental and social constrains. The decision-making variables of ISDWSP model are water demanded amount by different sectors and waterworks building scale. In the solution process, the ISDWSP is transformed into two deterministic sub-models, which correspond to the upper and lower bounds of the objective function, and the reasonable interval solution set in the given decision space can be obtained by solving the two sub-models. Thus, decision alternatives can be obtained by adjusting decision variable values within their solution intervals and will be useful for decision makers to choose the projected applicable conditions considering tradeoffs between eco-environmental and economic objectives. The model is also applied in a new developing zone of North China with the results of the case study providing reasonable solutions for dynamic planning of different source water (DSW) allocation in a regional system. Finally, waterworks building plan is generated based on the projected applicable conditions.     

Variable selection for market basket analysis

Results on cross category effects obtained by explanatory market basket analyses may be biased as studies typically investigate only a small fraction of the retail assortment (Chib et al. in Advances in econometrics, vol 16. Econometric models in marketing. JAI, Amsterdam, pp 57–92, 2002). We use Bayesian variable selection techniques to determine significant cross category effects in a multivariate logit model. Hence, we achieve a reduction of coefficients to be estimated which decreases computation time heavily and thus allows to consider more product categories than most previous studies. Next to the extension of numbers of categories, the second purpose of this paper is to learn about the capabilities of different variable selection algorithms in the context of market basket analysis. We present three different approaches to variable selection and find that an adaptation of a technique by Geweke (Contemporary Bayesian econometrics and statistics. Wiley, Hoboken, 2005) meets the requirements of market basket analysis best, namely high numbers of observations and cross category effects. For a real data set, we show (1) that only a moderate fraction of possible cross category effects are significantly different from zero (one third for our data), (2) that most of these effects indicate complementarity and (3) that the number of considered product categories influences significances of cross category effects.     

Optimal media planning for multi-products in segmented market

Promotion is an essential stage of any product life cycle. All firms either concerned with single or multiple products promote their products. Advertising is the most dominated form of promotion for most of the products. Our research focuses on firms which produces a multiple range of products and advertise them using available media options. The budget constraint forms the major restriction. The existing research in media allocation of multiple products ignores the market segmentation and formulates the media plan assuming all segments alike. In this paper we formulate a media planning problem for allocating the available budget in multiple media that are found suitable for the advertising of multiple products considering marketing segmentation aspect of advertising. The objective is to maximize the total reach in all the segments. Goal programming technique is used to solve the problem. A case study is presented to show the real life application of the model.     

An explicit formula for the solution of the Fisher-Wright selection model in population genetics

An explicit formula for the solution of the discrete version of the Fisher-Wright selection model is given. Mathematically, the equations of this model form a system of non-linear difference equations of first order.     

An advanced dynamic process model for industrial horizontal anode baking furnace

The global aluminum industry is facing new challenges due to new technological developments. Carbon anodes, consisting of mainly petroleum coke and coal tar pitch, are used in the electrolytic production of aluminum. High amperage utilization in the electrolytic cells with the objective of increasing production requires high quality carbon anodes. The anode quality depends both on raw material quality, anode recipe as well as forming and baking conditions of anode manufacturing process. The cost of the baking process constitutes 15 to 25% of the total aluminum production cost [1]. The industrial challenge is to produce better quality anodes consuming less energy, and reducing environmental emissions.A transient two dimensional (2D⁺) process model for horizontal anode baking furnace was developed during this study. The main objective was to develop an efficient furnace model with low computation load and time, using the transient Finite Difference Method and simplified furnace geometry. The model represents several phenomena involved during the anode baking process such as heat transfer (convection, radiation and conduction), fuel combustion, volatile matter (tar, methane and hydrogen) generation and combustion, air infiltration and energy loss to the atmosphere from the walls, the top of the furnace and the foundation. The model was developed using two coupled sub-models; the first one describes the thermal conduction through the solid materials (brick refractory wall, packing coke and anode block) as well as the volatile release, and the second one describes the gas flow, heat and mass transfer as well as the combustion of fuel and volatiles in the flue. Compared to the existing process models (where the gas flow in flue is assumed as unidirectional along the horizontal furnace direction), the present model also considers the gas flow in vertical direction and uses four vertical planes per pit section to predict the temperature of the solids. The model predicts 2D temperature distribution within the flue gas (xy plane) and the pit solid materials (yz plane) allowing then the prediction of the pseudo tridimensional distribution of the solid temperature. This model is a useful tool for the continuous monitoring of anode temperature and studying of the horizontal anode baking furnace behaviour. The effect of any change in operational parameters and the energy consumption on the furnace operation can be predicted.     

Robust mean variance portfolio selection model in the jump-diffusion financial market with an intractable claim

In this paper, a continuous-time robust mean variance model in the jump-diffusion financial market with an intractable claim is considered, in which the price processes of the assets not only are driven by the Brownian motion, but also have the Poisson jumps. By combining the martingale representation theorem and the quantile formulation method, an explicit closed-form solution of the robust mean-variance portfolio selection model is given under some suitable assumptions.     

An equivalent pipe network model for free surface flow in porous media

Free surface flow analysis in porous media is challenging in many practical applications with strong non-linearity. An equivalent pipe network model is proposed for the simulation and evaluation of free surface flow in porous media. On the basis of representative elementary volume with homogeneous pore-scale patterns, the pore space of the homogeneous isotropic porous media is conceptualized as a collection of capillary tubes. According to Hagen-Poiseulle's law and flux equivalence principle, equivalent hydraulic parameters and unified governing formulations for the pipe network model are deduced. The two-dimensional free surface flow problem is reduced to a one-dimensional problem of pipe networks and a one-dimensional procedure based on the finite element method is then developed by introducing a continuous penalized Heaviside function. The proposed equivalent pipe network model is verified with results from numerical solutions and laboratory-measured data available in the literature, and good agreements are obtained. The proposed equivalent pipe network model is shown to be effective in analyzing the free surface flow in porous media. The numerical results also indicate that the proposed equivalent pipe network model has weak sensitivity of the mesh size and penalty parameters.     

An analytical model for carrier-facilitated solute transport in weakly heterogeneous porous media

Carrier-facilitated solute transport in heterogeneous aquifers is studied within a Lagrangian framework. Dissolved solutes and carriers are advected by steady random groundwater flow, which is modeled by Darcy's law with uncertain hydraulic conductivity that is treated as a stationary random space function. We derive general expressions for the spatial moments of the dissolved concentration and the concentration associated with the carrier phase. In order to reduce the computational effort, we use previously derived solutions for the flow field. This enables us to obtain closed-form solutions for the spatial moments of the two concentration fields. The mass and center of gravity of the two propagating plumes depend only on the mean velocity field and chemical/degradation processes. The higher (second and third) moments are affected by the coupling between reactions (sorption/desorption and degradation) among the three phases (i.e., dissolved, carrier and sorbed concentrations) and the aquifer’s heterogeneity. We investigate the potentially enhancing effect of carriers by comparing spatial moments of the two propagating plumes. The forward/backward mass transfer rates between the liquid and carrier phases, and the degradation coefficients are identified as critical parameters. The carrier's role is most prominent when detachment from carrier sites is slow, provided that degradation on the carriers is smaller than that in the liquid phase.     

An automatic regularization parameter selection algorithm in the total variation model for image deblurring

Image restoration is an inverse problem that has been widely studied in recent years. The total variation based model by Rudin-Osher-Fatemi (1992) is one of the most effective and well known due to its ability to preserve sharp features in restoration. This paper addresses an important and yet outstanding issue for this model in selection of an optimal regularization parameter, for the case of image deblurring. We propose to compute the optimal regularization parameter along with the restored image in the same variational setting, by considering a Karush Kuhn Tucker (KKT) system. Through establishing analytically the monotonicity result, we can compute this parameter by an iterative algorithm for the KKT system. Such an approach corresponds to solving an equation using discrepancy principle, rather than using discrepancy principle only as a stopping criterion. Numerical experiments show that the algorithm is efficient and effective for image deblurring problems and yet is competitive.     

Forecasting model with asymmetric market response and its application to pricing of consumer package goods

This paper presents a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable—price promotion—by threshold models. As a threshold variable to generate a mechanism for different market responses, we use the counterpart to the concept of a price threshold applied to a representative consumer in a store. A Bayesian approach is taken for statistical modelling because of advantages that it offers over estimation and forecasting. The proposed model incorporates the lagged effects of a price variable. Thereby, myriad pricing strategies can be implemented in the time horizon. Their effectiveness can be evaluated using the predictive density. We intend to improve the forecasting performance over conventional linear time series models. Furthermore, we discuss efficient dynamic pricing in a store using strategic simulations under some scenarios suggested by an estimated structure of the models. Empirical studies illustrate the superior forecasting performance of our model against conventional linear models in terms of the root mean square error of the forecasts. Useful information for dynamic pricing is derived from its structural parameter estimates. This paper develops a dynamic forecasting model that accommodates asymmetric market responses to marketing mix variable—price promotion—by the threshold models. Copyright © 2005 John Wiley & Sons, Ltd.     

An EOQ model for deteriorating items in a declining market with SFI policy

An order-level inventory model fora perishable product with a timedependent demand is developed fora fixed planning period, allowing backlogging in all cycles within the said period. The market demand is assumed todecrease exponentially as time elapses. The average system cost is derived and its optimization procedure is illustrated with a numerical example. Sensitivity of the optimal solution to changes in the values of different parameters of the system is also analysed.     

An expected regret minimization portfolio selection model

Fuzzy portfolio selection has been widely studied within the framework of the credibility theory. However, all existing models provide only concentrated investment solutions, which contradicts the risk diversification concept in the classical portfolio selection theory. In this paper, we propose an expected regret minimization model, which minimizes the expected value of the distance between the maximum return and the obtained return associated with each portfolio. We prove that our model is advantageous for obtaining distributive investment and reducing investor regret. The effectiveness of the model is demonstrated by using an example of a portfolio selection problem comprising ten securities in the Shanghai Stock Exchange 180 Index.     

Optimal dividends in the dual model

The optimal dividend problem proposed by de Finetti [de Finetti, B., 1957. Su un’impostazione alternativa della teoria collettiva del rischio. In: Transactions of the XVth International Congress of Actuaries, vol. 2. pp. 433-443] is to find the dividend-payment strategy that maximizes the expected discounted value of dividends which are paid to the shareholders until the company is ruined or bankrupt. In this paper, it is assumed that the surplus or shareholders’ equity is a Lévy process which is skip-free downwards; such a model might be appropriate for a company that specializes in inventions and discoveries. In this model, the optimal strategy is a barrier strategy. Hence the problem is to determine b^∗, the optimal level of the dividend barrier. A key tool is the method of Laplace transforms. A variety of numerical examples are provided. It is also shown that if the initial surplus is b^∗, the expectation of the discounted dividends until ruin is the present value of a perpetuity with the payment rate being the drift of the surplus process.     

An optimization model for software component selection under multiple applications development

Component based software development (CBSD) is well acknowledged as a methodology which establishes reusability of software and reduce development cost effectively. While developing enterprise application using component based software engineering (CBSE) methods, software component selection plays a very important role in the process of component retrieval, adaptation and assembly. However, most of current researches focus on technical aspects from domain engineering and application engineering to improve reusability and system efficiency rather than application of optimization methods in CBSD management, especially application in component selection. Moreover, few existing researches have concerned about the situation where a software developer or enterprise develops multi-applications at the same time. By introducing the concept of reusability and a new formulation of compatibility matrix, an optimization model is proposed to solve component selection problem considering reusability and compatibility simultaneously. The model can be used to assist software developers in selecting software components when multi-applications are undertaken concurrently. Four experiments are conducted with the purpose to provide some insights in management perspective.