Metin Dağdeviren

Using the analytic network process (ANP) in a SWOT analysis - A case study for a textile firm

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis does not provide an analytical means to determine the importance of the identified factors or the ability to assess decision alternatives according to these factors. Although the analysis successfully pinpoints the factors, individual factors are usually described briefly and very generally. For this reason, SWOT analysis possesses deficiencies in the measurement and evaluation steps. Although the analytic hierarchy process (AHP) technique removes these deficiencies, it does not allow for measurement of the possible dependencies among the factors. The AHP method assumes that the factors presented in the hierarchical structure are independent; however, this assumption may be inappropriate in light of certain internal and external environmental effects. Therefore, it is necessary to employ a form of SWOT analysis that measures and takes into account the possible dependency among the factors. This paper demonstrates a process for quantitative SWOT analysis that can be performed even when there is dependence among strategic factors. The proposed algorithm uses the analytic network process (ANP), which allows measurement of the dependency among the strategic factors, as well as AHP, which is based on the independence between the factors. Dependency among the SWOT factors is observed to effect the strategic and sub-factor weights, as well as to change the strategy priorities.

Weapon selection using the AHP and TOPSIS methods under fuzzy environment

The weapon selection problem is a strategic issue and has a significant impact on the efficiency of defense systems. On the other hand, selecting the optimal weapon among many alternatives is a multi-criteria decision-making (MCDM) problem. This paper develops an evaluation model based on the analytic hierarchy process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS), to help the actors in defence industries for the selection of optimal weapon in a fuzzy environment where the vagueness and subjectivity are handled with linguistic values parameterized by triangular fuzzy numbers. The AHP is used to analyze the structure of the weapon selection problem and to determine weights of the criteria, and fuzzy TOPSIS method is used to obtain final ranking. A real world application is conducted to illustrate the utilization of the model for the weapon selection problem. The application could be interpreted as demonstrating the effectiveness and feasibility of the proposed model.

Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management

Safety management (SM) is a very important element within an effective manufacturing organization. One of the most important components of SM is to maintain the safety of work systems in the workplace. Safety of work systems is a function of many factors which affect the system, and these factors affect the safety of work systems simultaneously. For this reason, measuring work system safety needs a holistic approach. In this study, the work safety issue is studied through the analytic hierarchy process (AHP) approach which allows both multi-criteria and simultaneous evaluation. Another limitation faced in SM is the inability to measure the variables exactly and objectively. Generally, the factors affecting work system safety have non-physical structures. Therefore, the real problem can be represented in a better way by using fuzzy numbers instead of numbers to evaluate these factors. In this study, a fuzzy AHP approach is proposed to determine the level of faulty behavior risk (FBR) in work systems. The proposed method is applied in a real manufacturing company. In the application, factors causing faulty behavior are weighted with triangular fuzzy numbers in pairwise comparisons. These factors are evaluated based on the work system by using these weights and fuzzy linguistic variables. As a result of this evaluation FBR levels of work systems are determined and different studies are planned for work systems according to the FBR levels. In this way, faulty behavior is prevented before occurrence and work system safety is improved.

Decision making in equipment selection: an integrated approach with AHP and PROMETHEE

Multi-attribute equipment selection is a very important issue for an effective manufacturing system, since the improper equipment selection might cause many problems affecting productivity, precision, flexibility and quality of the products negatively. On the other hand, selecting the best equipment among many alternatives is a multi-criteria decision making (MCDM) problem. In this study, an integrated approach which employs analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluations (PROMETHEE) together, is proposed for the equipment selection problem. The AHP is used to analyze the structure of the equipment selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain final ranking, and to make a sensitivity analysis by changing the weights. Proposed approach is applied to a problem of selecting milling machines to be purchased in an international company. Company management found the application and results satisfactory and implementable in their equipment selection decisions.

Using the fuzzy analytic network process (ANP) for Balanced Scorecard (BSC): A case study for a manufacturing firm

Balanced Scorecard (BSC), which is used as a strategic evaluation tool, is a method of determining business performance using lagging and leading indicators on the basis of vision and strategies. The method suggests that business performance should be evaluated not only by using financial indicators but also simultaneously considering non-financial indicators. It has been revealed in the review of relevant literature that despite the satisfying levels achieved in conceptual and theoretical dimension of Balanced Scorecard, the method has some deficiencies in terms of implementation on a quantitative basis and that there remain some problems to be resolved. Subject of this study covered the measurement and evaluation dimension of BSC. In the scope of the study, BSC approach was integrated with fuzzy ANP technique so as to determine the performance level of a business on the basis of its vision and strategies. Proposed model has shown that performance indicators with different structures included in BSC approach can be consolidated with the help of fuzzy ANP technique.

A fuzzy analytic network process (ANP) model for measurement of the sectoral competititon level (SCL)

The purpose of this study is to measure the sectoral competition level (SCL) of an organization within the framework of Porters five forces analysis by using fuzzy analytic network process (ANP) technique. The framework of the study was based on two main thoughts: First is the necessity to approach to the problem on fuzzy logic basis because of complexity and vagueness, which are inherent in the nature of the competition concept. Second is the necessity to take into consideration the mutual interactions between factors as five forces analysis of Porter suggests so in order to determine SCL. In the scope of the study, firstly the factors and sub-factors which have an impact on the competition level were determined and then inner dependencies between models and factors were examined. The weights of sub-factors were determined on the basis of these examined dependencies and these weights were used for a case study to determine SCL.

A hybrid multi-criteria decision-making model for personnel selection in manufacturing systems

This study described a hybrid model for supporting the personnel selection process in manufacturing systems. Personnel selection is a very important issue for an effective manufacturing system, since the improper personnel might cause many problems affecting productivity, precision, flexibility and quality of the products negatively. On the other hand, selecting the best personnel among many alternatives is a multi-criteria decision making (MCDM) problem. In this study, a hybrid model which employs analytic network process (ANP) and modified TOPSIS (Technique for Order Performance by Similarity to Idea Solution) together, is proposed for the personnel selection problem. The ANP is used to analyze the structure of the personnel selection problem and to determine weights of the criteria, and modified TOPSIS method is used to obtain final ranking. To illustrate how the approach is used for the personnel selection problem, an application of a real case in a company is conducted. The application has demonstrated the effectiveness and feasibility of the proposed model. Company management found the application and results satisfactory and implementable in their personnel selection process.

A combined approach for equipment selection: F-PROMETHEE method and zero-one goal programming

With the labor and material, equipments will be used in production processes, are one of the essential components of the production systems. Equipments used in production process are an important subject, effecting the system efficiency, the labor effectiveness and the product quality, and using inappropriate equipment effects all of this issues negatively. Equipment selection is a very important point for an efficient production system and is a complex and exhaustive problem necessitating the most proper selection among the various types of equipments seeming almost identical, generally. Therefore, an equipment selection problem is a multi-criteria decision making problem entailing taking into account of several criteria and generally involving linguistic datas. In this study, a multi-criteria decision making problem compromising a ranking due to criterias expressed in a linguistic way, concerning a welding machine selection problem of a company is handled. The vagueness of the linguistic terms in the evaluation process required employment of fuzzy numbers and accordingly the fuzzy version of PROMETHEE method, which is a multi-criteria ranking technique, is applied to the selection problem. The information obtained from F-PROMETHEE results is then used as a constraint in formulating a zero-one goal programming model. We demonstrated how a combined F-PROMETHEE and ZOGP model can be used for a real world application problem as an aid for equipment selection.

A hybrid MCDM approach to assess the sustainability of students’ preferences for university selection

AbstractSelection of the most suitable university among many alternatives is a multi-criteria decision making (MCDM) problem. In this paper, an integrated approach which employs analytic network process (ANP) and preference ranking organization method for enrichment evaluations (PROMETHEE) together, is proposed for this problem. By the way, the paper is concerned with criteria influencing student choice in Turkey to establish if there is any need in developing a multi-criteria model for predicting students’ preference for universities. The ANP is used to analyse the structure of the university selection problem and to determine weights of the criteria, and the PROMETHEE method is used to obtain final ranking, and to make a sensitivity analysis by changing the weights for criteria. The results indicate that three factors, future career prospects and opportunities, scholarship and universitys social life at the top in the university selection.

A Fuzzy Multi-Attribute Decision Making Model for Strategic Risk Assessment

Abstract Risk assessment is a very important issue for an effective institution, since the lack of accurate risk assessment method or the improper risk management might cause problems to achieve institutions’ strategic objectives. There are a finite number of risks which have to be ranked considering many different and conflicting criteria. In this respect, assessing risks by relating to strategic objectives is a multi-attribute decision making problem. In this study, an integrated approach which employs analytic hierarchy process (AHP) and fuzzy logarithmic least squares method (LLSM) together is proposed for the strategic risk assessment problem. The AHP is used to analyze the structure of the risk assessment problem and to determine weights of the criteria, and fuzzy LLSM method is used to obtain final ranking. Proposed approach is applied to a problem of prioritizing risks in a public institution.