Product Selection Problem Research Articles

COTS selection using fuzzy interactive approach

In this paper, we introduce fuzzy mathematical programming (FMP) for decision-making related to software creation by selecting optimal commercial-off-the-shelf (COTS) products in a modular software system. Each module in such software systems have different alternatives with variations in their properties, for example, quality, reliability, execution time, size and cost. Due to these variations, component-based software developers generally deals with the problem of selecting appropriate COTS products. The development of COTS-based systems largely depends on the success of the selection process. Various crisp optimization models of COTS products selection have been proposed in literature. However, in real COTS products selection problem, it is difficult to estimate precisely the values of various model parameters due to lack of sufficient data and also because of measurement errors. Hence, instead of crisp optimization model, if we use flexible optimization model then we might obtain results which are more preferred by the decision maker. In this study, we use multiple methodologies such as quality model, analytical hierarchy process and FMP to develop fuzzy multiobjective optimization model of the COTS products selection. To determine a preferred compromise solution for the multiobjective optimization problem, an interactive fuzzy approach is used.

Fuzzy decision making of profit function in production planning using S-curve membership function

Any modern industrial manufacturing unit inevitably faces problems of vagueness in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by marketing department. Such a complex problem of vagueness and uncertainty can be handled by the theory of fuzzy linear programming. In this paper, a new fuzzy linear programming based methodology using a modified S-curve membership function is used to solve fuzzy mix product selection problem in Industrial Engineering. Profits and satisfactory level have been computed using fuzzy programming approach. Since there are several decisions to be taken, a performance measure has been defined to identify the decision for high level of profit with high degree of satisfaction.

FUZZY LINEAR PROGRAMMING FOR DECISION MAKING AND PLANNING UNDER UNCERTAINTY

In this paper, the S-curve membership function methodology is used in a real life industrial problem of mix product selection. This problem occurs in the chocolate manufacturing industry whereby a decision maker, analyst and implementer play important roles in making decisions in an uncertain environment. As analysts, we try to find a solution with a higher level of satisfaction for the decision maker to make a final decision. This problem of mix product selection is considered because all the coefficients such as objective, technical and resource variables are fuzzy. This is considered as one of the sufficiently large problem involving 29 constraints and 8 variables. A decision maker can identify which vagueness (α) is suitable for achieving satisfactory optimal revenue. The decision maker can also suggest to the analyst some possible and practicable changes in fuzzy intervals for improving the satisfactory revenue. This interactive process has to go on among the analyst, the decision maker and the implementer until an optimum satisfactory solution is achieved and implemented.

Fuzzy optimization of units products in mix-product selection problem using fuzzy linear programming approach

In this paper, the modified S-curve membership function methodology is used in a real life industrial problem of mix product selection. This problem occurs in the production planning management where by a decision maker plays important role in making decision in an uncertain environment. As analysts, we try to find a good enough solution for the decision maker to make a final decision. An industrial application of fuzzy linear programming (FLP) through the S-curve membership function has been investigated using a set of real life data collected from a Chocolate Manufacturing Company. The problem of fuzzy product mix selection has been defined. The objective of this paper is to find an optimal units of products with higher level of satisfaction with vagueness as a key factor. Since there are several decisions that were to be taken, a table for optimal units of products respect to vagueness and degree of satisfaction has been defined to identify the solution with higher level of units of products and with a higher degree of satisfaction. The fuzzy outcome shows that higher units of products need not lead to higher degree of satisfaction. The findings of this work indicates that the optimal decision is depend on vagueness factor in the fuzzy system of mix product selection problem. Further more the high level of units of products obtained when the vagueness is low.

INDUSTRIAL PRODUCTION PLANNING USING INTERACTIVE FUZZY LINEAR PROGRAMMING

Any modern industrial manufacturing unit inevitably faces problems of vagueness in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by marketing department. Such a complex problem of vagueness and uncertainty can be handled by the theory of fuzzy linear programming. In this paper, a new fuzzy linear programming based methodology using a modified S-curve membership function is used to solve fuzzy mix product selection problem in Industrial Engineering. Profits and satisfactory level have been computed using fuzzy linear programming approach. Since there are several decisions to be taken, a performance measure has been defined to identify the decision for high level of profit with high degree of satisfaction.

Decision making in industrial production planning using fuzzy linear programming

Any modern industrial manufacturing unit inevitably faces problems of vagueness in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by the marketing department. Such a complex problem of vagueness and uncertainty can be handled by the theory of fuzzy logic. In this paper, a new fuzzy logic based methodology using a S‐curve membership function is used to solve a fuzzy mix product selection problem in industrial engineering. Profits and satisfaction levels have been computed using a fuzzy linear programming approach. Since there are several decisions to be taken, a performance measure has been defined to identify the decision that achieves a high level of profit with a high degree of satisfaction.

Application of Fuzzy Linear Programming in Production Planning

In this paper, a new fuzzy linear programming based methodology using a specific membership function, named as modified logistic membership function is proposed. The modified logistic membership function is first formulated and its flexibility in taking up vagueness in parameters is established by an analytical approach. This membership function is tested for its useful performance through an illustrative example by employing fuzzy linear programming. The developed methodology of FLP has provided a confidence in applying to real life industrial production planning problem. This approach of solving industrial production planning problem can have feed back within the decision maker, the implementer and the analyst. In such case this approach can be called as IFLP (Interactive Fuzzy Linear Programming). There is a possibility to design the self organizing of fuzzy system for the mix products selection problem in order to find the satisfactory solution. The decision maker, the analyst and the implementer can incorporate their knowledge and experience to obtain the best outcome.

Product Selection and Investment Appraisal for Flexible Assembly

An approach has been developed for the solution of the flexible assembly product selection problem. Identifying suitable products for the system is achieved by a set of product selection criteria which is based on the technological adaptability and financial requirements of competing products. The method developed enhances early design stages by providing the most appropriate candidate product(s) and enabling an efficient system to be selected.

Two Stage (Perfect) Equilibrium in Hotelling's Model

HOTELLING [I 929] suggests that his spatial competition model can be used to describe a wide range of differentiation problems. He points to the selection of product variety within an industry as a potential application. Most of the subsequent work in his tradition has taken the equivalence of the two problems for granted. In this note, we look more closely at this equivalence. We distinguish between two types of differentiated products according to the variety of preferences assumed with respect to those products. Building on this distinction, we recognize that the demand faced by a firm locating on Hotelling's line is analogous to the demand faced by a firm selecting a horizontally differentiated product. It should be emphasized, thus, that the equivalence between the geographical and the product selection problem is by no means general and relies on specific assumptions about consumers' preferences. Next, we formulate a small model, close to Hotelling's one in which firms select a horizontally differentiated product. Within this model, it will be shown that a pure strategy price equilibrium exists for every pair of products. This statement is to be contrasted with the results of d'Aspremont et al. [I979], who have shown that in the original Hotelling's setting an equilibrium fails to exist when firms are too close together. 1 In addition, we will examine the product selection problem faced by firms in a two-stage game: in the first stage, each firm selects a product; in the second stage, the firm defines a price for its product. We will seek the existence of a perfect equilibrium in this game. A perfect equilibrium in this context can be viewed as a Nash equilibrium in a game in which firms select a product, aware of the non-cooperative price equilibrium that will occur for each of their choices. It will be shown that contrary to Hotelling's principle, the two firms will maximise their differentiation (i.e. firms will locate at opposite ends of the market).

Blue and Red Cars, or Blue Cars Only: A Note on Product Variety

The number and variety of products observed at any point of time in a given industry results from a complex selection mechanism where various economic forces interact. Some of these forces proceed from the demand behaviour of the market. For instance, the need for product variety should increase, the larger the degree of income or taste differences between consumers. Similarly, product variety may be more desirable from the consumer's viewpoint, the smaller the degree of substitutability between the quantity of a given product and its quality (a copious meal may not compensate for second-rate food). On the other hand, the opening of a new product line is generally accompanied by important overhead costs; these costs may lead to a restriction in the variety of goods that it would otherwise be desirable to produce. Sometimes also a firm in a given industry may be constrained by technical feasibility or institutional reasons to produce a single, or a restricted, set of products only, though in other industries multi-product firms are allowed to cover the whole spectrum of goods. The product selection mechanism arising in the two types of industries should differ since, in the first case, competition between product lines takes place between different firms, and, in the second, the same competition arises inside the firm. These reasons make the problem of product selection one of the most difficult subjects of monopolistic competition. In spite of this difficulty, recent work in the field has opened avenues for further research. Of particular interest is the study of the welfare implications of this selection mechanism, and its links with price or quality regulation policies. In this respect, contributions by Sheshinski (1976) and Spence (1975) have revealed that, when monopolists have latitude in determining the quality attribute of their product, profit-maximizing decisions generally deviate from the social optimum in terms of quality assessments. On the other hand, Stern (1974) and Meade (1974) have provided examples showing that the variety of products that should be produced according to welfere criteria does not always coincide with the combination of products that is profitable to produce in an unregulated market. It is with these contributions that the present paper is concerned. The difference between social optimum and profitability is imputed by Meade to the interaction between two major forces: