Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Vendor Selection and Supply Quotas Determination by Using the Analytic Hierarchy Process and a New Multi-objective Programming Method

In this article, we propose a new methodology for solving the vendor selection and the supply quotas determination problem. The proposed methodology combines the Analytic Hierarchy Process (AHP) for determining the coefficients of the objective functions and a new multiple objective programming method based on the cooperative game theory for vendor selection and supply quotas determination. The proposed methodology is tested on the problem of flour purchase by a company that manufactures bakery products. For vendor selection and supply quotas determination we use three complex criteria: (1) purchasing costs, (2) product quality, and (3) vendor reliability

Performance Measurement Model for the Supplier Selection Based on AHP

The performance of the supplier is a crucial factor for the success or failure of any company. Rational and effective decision making in terms of the supplier selection process can help the organization to optimize cost and quality functions. The nature of supplier selection processes is generally complex, especially when the company has a large variety of products and vendors. Over the years, several solutions and methods have emerged for addressing the supplier selection problem (SSP). Experience and studies have shown that there is no best way for evaluating and selecting a specific supplier process, but that it varies from one organization to another. The aim of this research is to demonstrate how a multiple attribute decision making approach can be effectively applied for the supplier selection process

The Application of a Decision-making Approach Based on Fuzzy ANP and TOPSIS for Selecting a Strategic Supplier

Supplier selection becomes very important when used in the context of strategic partnerships because of the long-term orientation of the relationship. This paper describes the application of a decision-making approach for selecting a strategic partner (supplier). The approach starts with defining a set of criteria that fits the company's condition. In the next steps, a combination of fuzzy-ANP and TOPSIS methods is used to determine the weight for each criterion and rank all the alternatives. The application of the approach in an Indonesian manufacturing company showed that the three factors that got the highest weight were “geographical location”, “current operating performance”, and “reliability”. Geographical location got the highest weight because it affects many other factors such as reaction to changes in demand, after-sales service, and delivery lead-time. Application of the approach helps decision-makers to gain effectiveness and efficiency in the decision-making process because it facilitates them to express their group's collective preferences while also providing opportunities for members to express their individual preferences. Future research can be directed at combining qualitative and quantitative criteria to develop the best criteria and methods for the selection of the best suppliers based on fuzzy ANP and TOPSIS

Multi-criteria decision making approach for vendor selection

In the present study an efficient Multi-Criteria Decision Making (MCDM) approach has been proposed for quality evaluation and performance appraisal in vendor selection. Vendor selection is a Multi-Criteria Decision Making (MCDM) problem influenced by multiple performance criteria/attributes. These criteria attributes may be both qualitative as well as quantitative. Qualitative criteria estimates are generally based on previous experience and expert opinion on a suitable conversion scale (Likert Scale). This conversion is based on human judgment;therefore, predicted result may not be accurate always because the method doesn’t explore real data. These are analyzed using AHP, QFD, Fuzzy techniques etc. reported in literature. In solution of MCDM problems there should be a common trend is to convert quantitative criteria values into an equivalent single performance index called Multi-attribute Performance Index (MPI). Benchmarking and selection of the best alternative can be made in accordance with the MPI values of all the alternatives. In this context, present study highlights application of VIKOR method adapted from MCDM for utilizing quantitative real performance estimate scores. Detail methodology of VIKOR method has been illustrated in this reporting through a case study

Prioritizing Offshore Vendor Selection Criteria for the North American Geospatial Industry

The U.S. market for geospatial services totaled US $2.2 billion in 2010, representing 50% of the global market. Data-processing firms subcontract labor-intensive portions of data services to offshore providers in South and East Asia and Eastern Europe. In general, half of all offshore contracts fail within the first 5 years because one or more parties consider the relationship unsuccessful. Despite the high failure rates, no study has examined the offshore vendor selection process in the geospatial industry. The purpose of this study was to determine the list of key offshore vendor selection criteria and the efficacy of the analytic hierarchy process (AHP) for ranking the criteria that North American geospatial companies consider in the offshore vendor selection process. After the selection of the initial list of factors from the literature and their validation in a pilot study, a final survey instrument was developed and administered to 15 subject matter experts (SMEs) in North America. The SMEs expressed their preferences for one criterion over another by pairwise comparisons, which served as input to the AHP procedure. The results showed that the quality of deliverables was the top ranked (out of 26) factors, instead of the price, which ranked third. Similarly, SMEs considered social and environmental consciousness on the vendor side as irrelevant. More importantly, the findings indicated that the structured AHP process provides a useful and effective methodology whose application may considerably improve the quality of the overall vendor selection process. Last, improved and stabilized business relationships leading to predictable budgets might catalyze social change, supporting stable employment. Consumers could benefit from derivative improvements in product quality and pricing

The Application of a Decision-making Approach based on Fuzzy ANP and TOPSIS for Selecting a Strategic Supplier

Supplier selection becomes very important when used in the context of strategic partnerships because of the long-term orientation of the relationship. This paper describes the application of a decision-making approach for selecting a strategic partner (supplier). The approach starts with defining a set of criteria that fits the company's condition. In the next steps, a combination of fuzzy-ANP and TOPSIS methods is used to determine the weight for each criterion and rank all the alternatives. The application of the approach in an Indonesian manufacturing company showed that the three factors that got the highest weight were "geographical location", "current operating performance", and "reliability". Geographical location got the highest weight because it affects many other factors such as reaction to changes in demand, after-sales service, and delivery lead-time.  Application of the approach helps decision-makers to gain effectiveness and efficiency in the decision-making process because it facilitates them to express their group's collective preferences  while also providing opportunities for members to express their individual preferences. Future research can be directed at combining qualitative and quantitative criteria to develop the best criteria and methods for the selection of the best suppliers based on fuzzy ANP and TOPSIS