ارزیابی تامین کننده و تخصیص تقاضا در میان تامین کنندگان در زنجیره تامین

This paper presents a hybrid algorithm that prioritizes the suppliers and then allocates the demand among the suppliers. The objective here is to maximize the total purchase value of the items taking into consideration budget constraint, demand condition, delivery lead-time and supplier capacity. Since the problem is multi-criteria decision making, we solve this problem by integrating the supplier rating with mixed linear integer programming method. The customer demand is allocated by using a hybrid algorithm based on the technique for order preference by similarity to ideal solution (TOPSIS) and the mixed linear integer programming (MILP) approaches. The effectiveness of the proposed algorithm is validated with computational results. Drawing to a case, a supplier S3 is identified as the best supplier by using the TOPSIS method for demand allocation under no restrictions. On the contrary, under constrained scenario, supplier S2 is selected as the best supplier by using the hybrid algorithm for demand allocation and maximum units are allocated to S2.

Supply chain management, the process of planning, executing and controlling the operations of supply chain network, includes procurement of material, conversion of raw material into finished goods and distribution of finished goods to customers in such a way that it fulfils the demand of customer as efficiently as possible. A typical manufacturer spends approximately 60% of total income from sales on procurement of material such as raw material, intermediate parts, and components (Krajewski et al., 2007). Furthermore, procurement of goods and services constitutes up to 70% of product cost (Ghodsypour and O׳Brien, 1998). These stylized facts indicate that procurement of raw materials and components is one of the most important constituents of a supply chain, which facilitates any organization for achieving its goal of increasing the value creation by minimizing the cost. In procurement management, supplier selection is one of the important decision-making areas that enhance the purchase value in term of cost, quality and on-time delivery of the items purchased. Furthermore, companies are also facing tough competition from their rivals. To overcome this competitive pressure, companies are paying more attention to core competencies. They have increased their level of outsourcing, and are relying predominantly on their supply chains as the source of competitive advantage. Purchasing is an important function of supply chain management. The literature in this context significantly focused on choosing the right suppliers and allocating the appropriate demand of items to these suppliers. In an increasingly competitive environment, firms are paying more attention to selecting the right suppliers for procurement of raw materials and component parts for their products. Choi and Hartley (1996) reported that supplier evaluation and selection together has an important role in the supply chain process and is crucial to the success of a manufacturing firm. The present research work focuses on this issue of supply chain management. The main objective of the study is to address the problem of optimal allocation of demand of items among candidate suppliers in order to maximize the purchase value of items. The purchase value of the items directly relate to cost and quality of raw materials purchased from the supplier. Supplier selection problem is a multi-criteria decision making problem involving both qualitative and quantitative performance measures. Usually, several conflicting criteria make the supplier selection problem a complex problem. It is often desirable to make a compromise among the conflicting criteria. In this study, a new hybrid algorithm has been developed to solve the problem of multi-criteria customer demand allocation among more suppliers under budget, demand, delivery lead-time and supplier capacity constraints. The remainder of the paper comprises seven sections. Section 2 provides the review of literature on supplier selection. Section 3 identifies the research issues, which form the basis for problem formulation in the present research work and further presents the objective of the study. Section 4 discusses the technique for order preference by similarity to ideal solution (TOPSIS) used in the study and proposes the hybrid algorithm to solve the multi-criteria demand allocation problem. Section 5 presents the conceptual model of demand allocation among suppliers. Section 6 reports the case study and the findings of the computational experiments. Section 7 concludes the study along with future research directions.

The present research work aimed at providing a new direction to the supplier selection problem. A pool of suppliers was selected and the demand allocated optimally among the suppliers. In this scenario, the buyer company did not depend upon the single supplier. This should be encouraging to the managers interested in improving the reliability of the suppliers as well as quality of the items by creating the competition among the suppliers, maximization their value of procurement, and switch over to the demand from one supplier to another supplier when the first supplier is not capable of supplying the items due to unavoidable circumstances. Further, a pool of suppliers can help the managers for operating their supply chain smoothly without any breakdown due to the non-availability of the items not supplied by one of the supplier. The present research work will be helpful for the managers who are interested to reconfigure their supply chain under the failure of any supply chain partner or in a changing business environment. The proposed model is supportive for the managers as they can adjust the value of variables in the model as per their choices and determine the optimal quantity for allocation among rest of the suppliers. The proposed demand allocation model is easy to use as it is solved by the Lindo software. The model provides flexibility to the managers for evaluation of the different available alternatives in order to take a decision of optimal demand allocation among the suppliers. An important feature of the proposed hybrid model is its ability to capture qualitative as well as quantitative criteria consistent with the real world situations. In the model, TOPSIS method is used to decide the rating of the supplier and handle qualitative as well as quantitative criteria. The rating of the suppliers is decided by the closeness index, which is computed by TOPSIS. According to the closeness index; the managers can determine not only the rating of the suppliers but also they can assess the status of all possible suppliers. Hence, this feature of the model would help the managers in their decisions pertaining to supplier evaluation as well as demand allocation among the suppliers. In real supplier selection problems, the modeling of many situations may not be sufficient or exact, as the available data are inexact, vague, imprecise and uncertain by nature. In these situations, managers usually face a high degree of uncertainties and fuzzy-set theory is the most effective method for managing the vagueness and uncertainties of the problems. In this situation, the proposed fuzzy TOPSIS method is beneficial for the managers and it can capture their subjective estimates in terms of linguistic variables. In fact, the fuzzy TOPSIS method is very flexible and it can handle both tangible as well as intangible attributes and select the suitable suppliers effectively. Further, integration of fuzzy TOPSIS with MILP provides an opportunity to the managers to optimize their decision about optimal demand allocation among suppliers. Significantly, the proposed hybrid (fuzzy, TOPSIS and MILP) model provides more objective information for supplier evaluation and demand allocation among suppliers in supply chain The conceptual model of demand allocation supports the customer requirement and voice of stakeholders during the decision making. This feature of the proposed model definitely would help the manager to enhance the satisfaction level of its customers as well as stakeholders. The managers can use the proposed model to the analysis of other management decision making problems. The supply chain network is witnessing a changing business environment due to government policies aimed promoting new small manufacturing enterprises (SMEs) for intermediate parts and components. Hence, the managers have an option to select the new pool of suppliers and allocate the demand among new pool of suppliers in order to maximize their purchase value. In this context, the proposed hybrid model would be beneficial for the managers to operate their supply chain effectively and efficiently. Supplier selection and demand allocation is the process by which a company identifies, evaluate, and allocate the demand to the suppliers. The supplier selection process deploys tremendous amount of financial resources. In response, firm expects significant benefit from the suppliers offering high procurement value. The present research work describes the typical steps of supplier selection and demand allocation process, namely identification of objective of the firm, market opportunities, suppliers, computation of supplier rating, and demand allocation among the suppliers. It demonstrates how these steps are integrated together in order to achieve the maximum procurement value. The result of the experimental computation reveals that the proposed model will not only help the managers in resolving the uncertainty on supply chain management but also helps in finding out the better suppliers for supply chain. In case of change in demand, suppliers and items the managers can change the input parameters used in the model and allocate the demand among the supplier that maximizes the procurement value. In this context, the proposed model is easy to use and reliable for the supply chain managers. Continuous research for improvement in the existing system/practice has been the basic nature of human beings. Supplier evaluation and selection has always remained as an interesting area for research and has received worldwide attention over the past few decades. Diversified problems encountered by the real time manufacturing systems and the complex nature of the problem in itself pursued to be achieved have been the sources of motivation in supplier evaluation and selection research. The study on supplier evaluation and demand allocation among suppliers presented in this research paper could be extended in various ways. Firstly, more case studies on manufacturing systems engaged in diversified operations could underline the practical usefulness of the hybrid methodology as derived from the experimental results. Secondly, future research could consider the transportation cost during demand allocation among candidate suppliers. Thirdly, multi-period instead of single period demand allocation in supplier selection problem could be taken up. Finally, research can be extended by developing more hybrid approaches for demand allocation among suppliers.