Gin-Shuh Liang

Fuzzy MCDM based on ideal and anti-ideal concepts

This paper presents a novel fuzzy multiple criteria decision making (MCDM) based on the concepts of ideal and anti-ideal points. The concepts of fuzzy set theory and hierarchical structure analysis are used to develop a weighted suitability decision matrix to evaluate the weighted suitability of different alternatives versus various criteria. The distance of different alternatives versus positive ideal solution and negative ideal solution are then obtained by using the proposed ranking method. Finally, the relative approximation values of various alternatives versus positive ideal solution are ranked to determine the best alternative.

A fuzzy multi-criteria decision-making method for facility site selection

Abstract In this paper, a facility site selection algorithm is proposed. The algorithm based on the concepts of fuzzy set theory and the hierarchical structure analysis to aggregate decision-makers’ linguistic assessments about criteria weightings and the suitability of facility sites versus various selection criteria to obtain fuzzy suitability indices. Then rank the suitability ratings to determine the best facility site selection. By utilizing this decision algorithm, the decision-makers’ fuzzy assessments with various rating attitudes and the trade-off among various selection criteria can be taken into account in the aggregation process to asssure more convincing and accurate decision-making.

Using fuzzy MCDM to select partners of strategic alliances for liner shipping

As world economic activities intensify and trade barriers fall, the formation of viable strategic alliances in the liner shipping industry gains importance and accelerates of necessity. However, the selection of a suitable partner for strategic alliance is not an easy decision, involving a host of complex considerations. Decision-making information is hard to come by and often vague, particularly regarding privately held companies. Fuzzy set theory was designed to sort through the uncertainties of vague linguistic terms and help generate a single possible outcome. This research paper proposes the utilization of the fundamental principles encompassed in the fuzzy set theory to analyze and consider a multiplicity of complex criteria and determines the most suitable partner in strategic shipping alliances. The fundamental emphasis of the current fuzzy multiple criteria decision-making (FMCDM) methodology is the determination, definition, testing and comparison of complex multi-level criteria used in the partnership selection process. The tools and formulas employed are: (1) triangular fuzzy numbers and linguistic values characterized by triangular fuzzy numbers which are used to evaluate the preference rating system; (2) the method of graded mean integration, and the entropy weighting method which are jointly used to adjust integration weights of all sub-criteria above those of the alternatives; (3) the concepts of ideal and anti-ideal solutions which are employed to calculate the relative closeness of the various alternatives versus ideal solutions to rank their priorities, and finally, to determine the best alternative. We design a hypothetical problem in selecting partners of strategic alliances for liner shipping to demonstrate the computational process of this FMCDM algorithm. The main contribution of this paper is that the definition, conversion, and treatment of vague and complex multi-level criteria as set memberships under the fuzzy set theory are employed to develop a practical model for business purpose.

APPLICATION OF A FUZZY MULTI-CRITERIA DECISION-MAKING MODEL FOR SHIPPING COMPANY PERFORMANCE EVALUATION

Combining fuzzy set theory, Analytic Hierarchy Process (AHP) and concept of entropy, a fuzzy Multiple Criteria Decision-Making (MCDM) model for shipping company performance evaluation is proposed. First, the AHP is used to construct subjective weights for all criteria and sub-criteria. Then, linguistic values characterized by triangular fuzzy numbers and trapezoidal fuzzy numbers are used to denote the evaluation values of all alternatives with respect to various subjective and objective criteria. Finally, the aggregation fuzzy assessment of different shipping companies is ranked to determine the best selection. Utilizing this fuzzy MCDM model, the decision-makers fuzzy assessment and the trade-off between various evaluations criteria can be taken into account in the aggregation process, thus ensuring more effective and accurate decision-making.

Controlling inventory by combining ABC analysis and fuzzy classification

The objective of inventory management is to make decisions regarding the appropriate level of inventory. In practice, all inventories cannot be controlled with equal attention. The most widespread used inventory system is the ABC classification system, but the limitation of the ABC control system is that only one criterion is considered. The purpose of this paper is to propose a new inventory control approach called ABC-fuzzy classification (ABC-FC), which can handle variables with either nominal or non-nominal attribute, incorporate managers experience, judgment into inventory classification, and can be implemented easily. Our ABC-FC approach is implemented based on the data of the Keelung Port. The results of our study show that 59 items are identified as very important group, 69 items as important group, and the remaining 64 items as unimportant group. By comparing the results of ABC-FC with the original data, we find that our ABC-FC analysis shows a high accuracy of classification. Some concluding remarks and suggestions for inventory control are also provided.

Fuzzy fault-tree analysis using failure possibility

Abstract In conventional probability-based fault-tree analysis, the vague property in many systems, especially, the man-machine system is often ignored. To overcome this disadvantage, the fuzzy set theory is applied to fault-tree analysis. The failure possibility defined by a triangular fuzzy number on the interval [0,1] is used to characterize the possible deviation of the basic events. The fuzzy operations according to the extension principle is used to calculate the failure possibility of the top event. Furthermore, a fuzzy importance index is proposed to demonstrate the contribution of a basic event to the safety improvement of the top event in a fuzzy environment.

A soft computing method of performance evaluation with MCDM based on interval-valued fuzzy numbers

This study presented a new performance evaluation method for tackling fuzzy multicriteria decision-making (MCDM) problems based on combining VIKOR and interval-valued fuzzy sets. The performance evaluation problem often exists in complex administrative processes in which multiple evaluation criteria, subjective/objective assessments and fuzzy conditions have to be taken into consideration simultaneously in management. Here, the subjective, imprecise, inexact and uncertain evaluation processes are modeled as fuzzy numbers by means of linguistic terms, as fuzzy theory can provide an appropriate tool to deal with such uncertainties. However, the presentation of linguistic expressions in the form of ordinary fuzzy sets is not clear enough [15,21]. Interval-valued fuzzy sets can provide more flexibility [4,14] to represent the imprecise/vague information that results, and it can also provide a more accurate modeling. This paper presents the interval-valued fuzzy VIKOR, which aims to solve MCDM problems in which the weights and performances of criteria are unequal by using the concepts of interval-valued fuzzy sets. A case study for evaluating the performances of three major intercity bus companies from an intercity public transport system is conducted to illustrate the effectiveness of the method.

Extensions of the multicriteria analysis with pairwise comparison under a fuzzy environment

Abstract Multicriteria decision-making (MCDM) problems often involve a complex decision process in which multiple requirements and fuzzy conditions have to be taken into consideration simultaneously. The existing approaches for solving this problem in a fuzzy environment are complex. Combining the concepts of grey relation and pairwise comparison, a new fuzzy MCDM method is proposed. First, the fuzzy analytic hierarchy process (AHP) is used to construct fuzzy weights of all criteria. Then, linguistic terms characterized by L–R triangular fuzzy numbers are used to denote the evaluation values of all alternatives versus subjective and objective criteria. Finally, the aggregation fuzzy assessments of different alternatives are ranked to determine the best selection. Furthermore, this paper uses a numerical example of location selection to demonstrate the applicability of the proposed method. The study results show that this method is an effective means for tackling MCDM problems in a fuzzy environment.

Applying fuzzy quality function deployment to identify service management requirements for an ocean freight forwarder

Abstract In this paper, a Fuzzy Quality Function Deployment (FQFD) to identify service management requirements for an ocean freight forwarder is developed. First, customer needs, with importance and satisfaction degrees, have been investigated, followed by the development of service management requirements for satisfying the observed customer needs. Furthermore, a fuzzy relation matrix to link service management requirements and customer needs based on cross-functional expertise is also constructed. The aggregated fuzzy assessments of various service management requirements are ranked to determine their importance priority. Finally, an empirical study for identifying the service management requirements of the ocean freight forwarder company is used to demonstrate the proposed approach.

BENEFIT/COST ANALYSIS USING FUZZY CONCEPT

ABSTRACT Two algorithms are proposed to perform benefit/cost analysts in a fuzzy environment. The first algorithm considers the fuzzy measure of benefit to cost ratio to select the optimal alternative group under the available funds. The second algorithm considers the fuzzy measure of incremental benefit to incremental cost ratio to choose the optimal investment alternative from several mutually exclusive investment alternatives. By using these algorithms, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision-making.