Design is a multi-criteria decision-making process under multiple constraints. In the conceptual design stage, design is intrinsically imprecise because of designers’ vague thinking and incomplete initial information. When exploring possible design candidates, designers are generally more interested in sets of the most promising solutions rather than the best single solution. Therefore, in cont...

Supplier evaluation and selection is a critical decision process for companies in order to gain competitive advantage. Decision models focusing on risk minimization have recently received increasing attention in supplier selection literature. In this paper, risk factors, which incorporate qualitative as well as quantitative data, are employed in fuzzy data envelopment analysis for obtaining eff...

Companies, organizations, governmental departments, and universities need to adopt globalization patterns for their generative survival in dynamic productive outputs. Such outputs are possible only after effective, rational, logical, and systematic treatment of all available input knowledge and information. These inputs mostly have imprecision, uncertainty, vagueness, incompleteness, and missin...

Companies, organizations, governmental departments, and universities need to adopt globalization patterns for their generative survival in dynamic productive outputs. Such outputs are possible only after effective, rational, logical, and systematic treatment of all available input knowledge and information. These inputs mostly have imprecision, uncertainty, vagueness, incompleteness, and missin...

The purpose of this paper is to present an application of fuzzy logic to cost-volume-profit (CVP) analysis. The conventional analytical tool cost-volume-profit, commonly called breakeven analysis (BE), is used widely in managerial decision making. In its basic form, CVP analysis examines sales prices, sales volume, variable costs and fixed costs in relation to target profit levels. This traditi...

We present an approach to learn fuzzy binary decision rules from ordinal temporal data where the task is to classify every instance at each point in time. We assume that one class is preferred to the other, e.g. the undesirable class must not be misclassified. Hence it is appealing to use the Variable Consistency Dominance-based Rough Set Approach (VC-DRSA) to exploit preference information abo...

In real projects, the trade-off between the project cost and the project completion time, and the environmental uncertainty are aspects of considerable importance for managers. For complex environment with more than one type of uncertainty, this paper presents three types of time–cost trade-off models, in which the project environment is described via introducing the fuzzy random theory. The ex...

Fuzzy random variable is a combination of fuzzy variable and random variable, and can characterize both fuzziness and randomness in the real world. The mean chance of a fuzzy random event is an important concept in fuzzy random optimization, just like the probability of a stochastic event in stochastic optimization and the credibility of a fuzzy event in fuzzy optimization. In fuzzy random prog...

To face the reality of practical multiple criteria problems usually possessing characters of fuzziness, and to consider group decision making with various subjective–objective backgrounds usually participating in decision-making process. In this paper, the experts’ opinions are described by linguistic terms which can be expressed in trapezoidal (or triangular) fuzzy numbers. To make the consens...

This paper presents interactive fuzzy programming for multi-level linear programming problems with fuzzy parameters. In fuzzy programming for multi-level linear programming problems, recently developed by Lai et al., since the fuzzy goals are determined for both an objective function and decision variables at the upper level, undesirable solutions are produced when these fuzzy goals are inconsi...