Recent information and communication developments caused that global organizations spread out their markets throughout the world. In this environment, local exclusive markets have been replaced with global competitive ones. Therefore, organizations must concentrate on their main operations to survive in such an environment. To do so, managers have intended to cooperate with some financial partners in long-term relations. In this paper, the aim is to develop a fuzzy analytic network process (ANP) model to evaluate the potential suppliers and select the best one(s) with respect to the vendor important factors. Additionally, ANP is developed by fuzzy sets theory to cover the indeterminacy of decisions made in this field. The authors have augmented the model with a non-linear programming model to elicit eigenvectors from fuzzy comparison matrices. Hybridization of these two concepts can model supplier selection problem in all circumstances and reaches the optimal choice. Finally, a numerical sample is used to validate the proposed model.
Nowadays, organizations have realized that it is necessary to consider some other issues, such as product quality and manufacturing procedures, rather than traditional factors like prices, production rate, etc. Overcoming these issues, the organizations can succeed and survive in the global competitive markets. To do so, they must concentrate on their main operations and organizational goals and managers have decided to outsource non-strategic operations. Outsourcing help organizations focus on the important factors affecting their main operations. However, some items like supplier selection procedure and criteria are considerably essential in outsourcing. Moreover, cost of parts and raw materials forms a major portion of enterprises’ expenditures in most industries. As it is declared, purchasing cost can make 70% of the production cost (Ghobadian, Stainer, & Kiss, 1993), and even exceeds 80% in hi-tech production environment (Weber, Current, & Benton, 1991). Therefore, proper purchasing strategies, and especially proper suppliers, can play a key role in management of successful organizations and it is worthwhile to invest on making appropriate decision on supplier selection.
Supplier selection is a complex decision making process in nature due to different parameters and various aspects which must be regarded. However, in a research performed by Verma and Pullman (1998), it is concluded that managers consider quality as the most important factor to select suppliers, though they actually select them regarding their costs. In a comprehensive study (Dickson, 1966); the author presents 23 criteria to select suppliers (Table 1); while some other different criteria are considered in the recently developed models. Moreover, some distinct factors are taken into account by Chou and Chang, 2008, Üstün and Demirtas, 2008 and Lee, 2008 which are generally based upon management concepts. The involved parameters have various statuses and can be either dependent or independent. In addition, it is not possible to assign exact values to these parameters in most cases. To tackle the problem, some of methods have been proposed among which analytic hierarchy process (AHP) (Saen, 2007a), Cluster Analysis (CA) (Bottani & Rizzi, 2007) and data envelopment analysis (DEA) (Braglia & Petroni, 2000) can be mentioned. Most of the proposed methods cannot completely model supplier selection problem in a suitable, practical manner. In this paper, a hybridization of analytic network process and fuzzy sets theory is proposed to model and solve the problem under uncertain nature of the decision making process which made the model more applicable for practical situations. The proposed model is enhanced with a non-linear programming model to elicit weights of comparisons from comparison matrices in the ANP structure.
Table 1.
Dickson’s criteria.
No. Suppliers selection criteria
1 Supplier’s suggested net price (including discounts and transportation costs)
2 Supplier’s qualitative capabilities
3 After sales services
4 Supplier’s delivery capabilities
5 Supplier’s geographical situation
6 Supplier’s financial status
7 Supplier’s capacity and production facilities
8 Supplier’s partnership antecedents
9 Supplier’s technical capacity (including R&D capabilities)
10 Supplier’s organization and management
11 Future potential purchases from supplier
12 Supplier’s information system (with processing information)
13 Supplier’s operational control (including reporting, quality control, and inventory control system)
14 Supplier’s status in related industry (including credit and leadership)
15 Supplier’s individuals antecedents
16 Supplier’s organizational behavior
17 Supplier’s eagerness to cooperate
18 Supplier’s policy of guarantee and legal claims
19 Supplier’s capability to meet the product requirements
20 Effects of supplier’s contract on other contracts
21 Suppliers educational aids corresponding products
22 Supplier’s adaptation with the purchaser’s procedures and instruments
23 Supplier’s performance antecedents
Table options
The structure of this paper is as follows: Section 2 reviews the literature of the problem. Section 3 describes analytic network process in detail. The paper follows in Section 4 on the proposed algorithm. Section 5 illustrates a numerical example to validate the proposed algorithm. Finally, Section 6 comprises some results and remarking conclusions.
As today competitive market has had a growing trend through diverse industries and businesses, outsourcing has become a valuable option to help organizations concentrate on their main activities and move toward a more specialized context. Under such circumstances, partnership concepts and their requirements have come to existence, among which supplier selection is one of the most attracting areas to which a lot of researches have been devoted. In this paper, a framework based upon analytic network process is developed. The proposed framework is adopted, because it can suitably model the quantitative and qualitative criteria which are involved in supplier selection. The proposed model is enhanced with fuzzy sets theory to cope with the vagueness and indeterminacy of data. Moreover, a non-linear programming model is augmented to the proposed model to elicit the relative weights from fuzzy comparison matrices. Finally, a test problem is solved using the proposed model to show how it can be implemented and a sensitivity analysis is performed to study the model adequacy in facing with different conditions.
To extent the proposed model in this paper, the most practical case might be integration of the proposed framework with a suitable model to tackle order allocation as well as supplier selection. Then, the new hybrid model can be validated with respect to the proposed hybrid decision making models in the literature of supplier selection and order allocation.
