zahra jafari soruni

In today's competitive economy, the supply of a product in an optimal quantity, quality and minimum cost at the right time are the pillars of success in a business. A continually efficient supply chain also plays an important role in solidifying this success. This research aims to model an integrated supply chain network to achieve maximum profit while minimizing the overall response time.

In view of the importance of supply chain management and logistics in recent times, the design and optimization of the supply chain network are extremely critical. This is mostly because, at each decision level, a well-optimized decision will result in a competitive advantage in the market.  In this research, the said design and optimization is explained in two levels; a strategic level where a supply chain is designed, and a tactical level dedicated to operational planning of the supply chain. In this paper, a mathematical model has been formulated for these levels. To verify and validate the proposed model, the acquired data from a computer case manufacturing company are examined and the outcomes were highlighted.

This paper provides a tool in order to optimize the supply chain network. This tool can be useful for any manager or for those who are planning a supply chain from production or designing a product distribution network. Managers can also use this model to ensure the performance parameters of a particular supply chain.

The results show that the proposed model can provide an effective and easy-to-follow method to achieve a well-established plan in an integrated supply chain

One of the key decisions in organizations is the selection of suppliers. Typically, a list of identified suppliers is evaluated based on a set of criteria, which indicates a multi-criteria decision-making problem. There are multiple methods and multiple criteria for evaluating suppliers. The nature of such decisions is complex in conditions of uncertainty. The purpose of this study is to provide a method for evaluating suppliers in conditions of uncertainty. In this research, evaluation criteria are extracted from the supplier potential matrix, and after determining the importance of criteria using the Best-Worst Method, the degree of uncertainty is calculated with Gray Relational analysis and finally, Dempster-Shafer method is used to rank suppliers. Research data has been gathered from hardware industry experts, with knowledge and experience in purchasing and procurement. A real case study is presented to illustrate the proposed hybrid approach to supplier selection. In the capability dimension, quality and capacity of the warehouse and in the willingness dimension, willingness to share information and mutual interaction are respectively the best and worst indicators. Also, the ranking of suppliers was conducted in conditions of uncertainty. Research results are important from a few perspectives. First, the criteria presented are public and can be used in different industries and conditions. Second, gray relational analysis is used to calculate uncertainty, which is due to the use of less data.