Ziya Ulukan

MULTI-CRITERIA SUPPLIER SELECTION USING FUZZY AHP

A supplier selection decision inherently is a multi‐criterion problem. It is a decision of strategic importance to companies. The nature of this decision usually is complex and unstructured. Management science techniques might be helpful tools for these kinds of decision‐making problems. The aim of this paper is to use fuzzy analytic hierarchy process (AHP) to select the best supplier firm providing the most satisfaction for the criteria determined. The purchasing managers of a white good manufacturer established in Turkey were interviewed and the most important criteria taken into account by the managers while they were selecting their supplier firms were determined by a questionnaire. The fuzzy AHP was used to compare these supplier firms.

Justification of manufacturing technologies using fuzzy benefit/cost ratio analysis

The application of discounted cash flow techniques for justifying manufacturing technologies is studied in many papers. State-price net present value and stochastic net present value are two examples of these applications. These applications are based on the data under certainty or risk. When we have vague data such as interest rate and cash flow to apply discounted cash flow techniques, the fuzzy set theory can be used to handle this vagueness. The fuzzy set theory has the capability of representing vague data and allows mathematical operators and programming to apply to the fuzzy domain. The theory is primarily concerned with quantifying the vagueness in human thoughts and perceptions. In this paper, assuming that we have vague data, the fuzzy benefit–cost (B/C) ratio method is used to justify manufacturing technologies. After calculating the B/C ratio based on fuzzy equivalent uniform annual value, we compare two assembly manufacturing systems having different life cycles.

Using triangular fuzzy numbers in the tests of control charts for unnatural patterns

The control chart in essence is a set of statistical limits applied to a sequence of points representing a process under study. The data comprising each individual point are random, but the points themselves are plotted in some deliberately chosen non-random arrangement selected to represent the most important variable. The control chart tests the arbitrary or non-random arrangements of points to determine whether they behave as if they were random. If the plotted points indicate nothing but randomness, this tends to show that the variable which formed the base of the arrangement is not a significant variable. On the other hand, if the points indicate that non-randomness has entered the data, this tends to show that the variable on which the arrangement was based is actually a significant variable. The control chart tells when to look for trouble but it cannot, by itself, tell where to look or what cause will be found. The most important inadequacy of control charts is the case where all the points characterizing the process fall inside the limits even though the process is out of control. In such a case, one has an unnatural pattern. Some tests for unnatural patterns are given in most quality control books. These tests are applied by using a control charts of 60 divided into six equal zones. The authors propose an alternative method in this paper. Instead of using six equal zones of 1/spl sigma/ each, the authors use the corresponding degrees of membership of these zones.

Fuzzy flexibility analysis in automated manufacturing systems

Some researchers propose systematic procedures for quantifying flexibility in monetary terms and use financial evaluation models with decision criteria based on present worth, equivalent uniform annual worth, and the other discounting techniques. Many parameters are defined while quantifying flexibility value and are assumed to be accurate numerical estimates. But it must be considered that some changes in these numerical estimates may occur. Therefore, these parameters can be defined as triangular parameters. Thus, we obtained the fuzzy present worth formulas of the flexibility elements. Using these formulas, more reliable results can be obtained. The flexibility modeling using triangular fuzzy numbers allows experts linguistic predicate about automated manufacturing systems. Taking the result of the fuzzy present worth formula of the flexibility, the fuzzy flexibility evaluation can be achieved by applying some dominance rules on triangular fuzzy numbers.

Economic analyses for the evaluation of is projects

Information system projects usually have numerous uncertainties and several conditions of risk that make their economic evaluation a challenging task. Each year, several information system projects are cancelled before completion as a result of budget overruns at a cost of several billions of dollars to industry. Although engineering economic analysis offers tools and techniques for evaluating risky projects, the tools are not enough to place information system projects on a safe budget/selection track. There is a need for an integrative economic analysis model that will account for the uncertainties in estimating project costs benefits and useful lives of uncertain and risky projects. The fuzzy set theory has the capability of representing vague data and allows mathematical operators and programming to be applied to the fuzzy domain. The theory is primarily concerned with quantifying the vagueness in human thoughts and perceptions. In this article, the economic evaluation of information system projects using fuzzy present value and fuzzy B/C ratio is analyzed. A numerical illustration is included to demonstrate the effectiveness of the proposed methods.

Applications of Fuzzy Capital Budgeting Techniques

Summary. In an uncertain economic decision environment, an experts knowledge about dicounting cash flows consists of a lot of vagueness instead of randomness. Cash amounts and interest rates are usually estimated by using educated guesses based on expected values or other statistical techniques to obtain them. Fuzzy numbers can capture the difficulties in estimating these parameters. In this chapter, the formulas for the analyses of fuzzy present value, fuzzy equivalent uniform annual value, fuzzy future value, fuzzy benefit-cost ratio, and fuzzy payback period are developed and some numeric examples are given. Then the examined cash flows are expanded to geometric and trigonometric cash flows and using these cash flows fuzzy present value, fuzzy future value, and fuzzy annual value formulas are developed for both discrete compounding and continuous compounding. Finally, a fuzzy versus stochastic investment analysis is examined by using the probability of a fuzzy event.

Probabilistic cash flows and equivalent discount rates

Many authors have studied probabilistic cash flows in recent years. They have introduced analytical methods which determine the probability distribution function of the net present value and internal rate of return of a series of random discrete cash flows; considered serially correlated cash flows and the uncertainty of future capital investment and reinvestment rates; and presented formulas for benefit-cost ratio for probabilistic cash flows. Others have studied the arithmetic of inflation corrections in evaluating real present values. Here, the expected value and the variance of a probabilistic cash flow are obtained by means of moments. Assuming that cash flows are probabilistic because only future discount rates (involving inflation, risk and other factors) are uncertain, we calculate the mean level of future discount rates equivalent to the risk degree in probabilistic cash flows. A numerical example is given.

Multi-criteria capital budgeting using FLIP

By using fuzzy linear programming (FLIP), tolerance intervals are used for calculating the availability of capital at each point in time. The main advantage, compared to the non-fuzzy problem formulation, is the fact that the decision maker is not forced into a precise formulation for mathematical reasons. Linear membership functions which monotonically increase or decrease in the tolerance interval are used because they can be handled quite easily. A numeric example is given.

Fuzzy economic and strategic design

When a range of alternative designs has been created, the designer is then faced with the problem of selecting the best one. There are a lot of economic evaluation methods that are with single criterion or multicriteria and deterministic or nondeterministic. The selected methods in the paper are the fuzzy present worth method for the economic analysis and the fuzzy scoring method for the strategic analysis. The triangular fuzzy numbers calculated are compared by a certain method. The method is applied to the economic and strategic design of motorcars.

An Input–Output Analysis Approach in Waste of Electrical and Electronic Equipments

The disposal of waste of electrical and electronic equipments (WEEE) represents the loss of large amounts of valuable resources, in particular metals and plastics. If these were to be recycled, it would not only divert the waste from disposal by limiting waste flows damage but would also reduce the need to use virgin raw materials. In this study, we focus on waste management and we concentrate on the recycling of mobile phones. Mobile phone components and their requirements in production phases such as energy, labor, and know-how are depicted in a matrix form inspired from the seminal work of Leontief and input–output (I–O) methodology which appears to be appropriate for analyzing waste management problem is presented. Thus, we propose numerically static I–O solutions in order to demonstrate the contribution of recycling of mobile phones into the economy. Particularly, we concentrate on the monetary IO table (MIOT) and environmental IO table (EIOT) with recycling and balance equations. By defining waste outputs as a new vector class, the classical I–O model has been improved.