جستجوی مقالات مرتبط با کلیدواژه "supplier selection" در نشریات گروه "صنایع"

Designing an efficient construction supply chain involves numerous complexities. Therefore, the imperative of designing an appropriate supply chain, considering the high diversity of resources (nonrenewable), holds significant importance.  Given the variable nature of the project environment, the dynamic progress of the project, and the risks associated with construction projects, the project may deviate from the scheduled timeline. On the other hand, the quality of resources plays a crucial role in the construction quality of construction projects. Therefore, in this study, a multi-objective mixed-integer programming model is proposed for the design of a two-echelon supply chain network in the construction industry. The objectives of the model include minimizing supply chain costs, minimizing deviation from resources time delivery, and maximizing the quality of resources. This framework is capable of dynamically scheduling resources in terms of timing and delivery, as well as selecting appropriate suppliers restricted to authorized facilities within a network. Both classical methods and the Benders Decomposition Algorithm are employed to solve the presented model. The problem was solved for three sizes. The Benders Decomposition Algorithm was able to efficiently solve the problem for all three sizes in a very short amount of time.

In this research, a mathematical model of scenario-based mixed integer programming is presented to model the problem of supplier selection and order allocation considering Disruption Risk and Business Volume Discount in a centralized supply chain. The considered supply chain is Bi-Level and contains one manufacturer and several suppliers and as well as There are two categories of suppliers: main suppliers and backup suppliers. As is clear, it is assumed that the unit costs of the main suppliers are lower than those of the backup suppliers. Also, it is assumed that the backup supplier supports disruption conditions if the manufacturer meets the minimum value set by the supplier under normal conditions. Supplier Disruptions are random and independent. It is assumed that the disruption is not due to the lack of raw materials to suppliers. Demand is considered denitive and the model is a single-criteria with the criterion of reducing the cost of all members of the supply chain. Also in the presented model, a single-period multi-product supply chain is considered. Due to the importance of supplier selection and the high impact of the cost of purchasing raw materials on the total cost of the product and its aggravation in the event of disruption, this issue was investigated. Also, by calculating the C-VaR using GAMS and analyzing the sensitivity of the result, We examined the impact of the decision-making risk attitude on the total cost of the supply chain as well as the costs of each member and found out that increasing the decision-makers sensitivity to risk generally increases the this costs. We also examined this eect on purchases from suppliers. The result was that as the sensitivity to risk increased, the quantities purchased from undisturbed suppliers, whether main or backup, increased, but the quantities purchased from disrupted suppliers decreased. Also, in order to evaluate the eciency of the model, a case study was conducted in Sapco(Iran Khodro Engineering Design and Parts Supply Company).

The COVID-19 pandemic has led to a significant crisis in society's health, industries, and businesses. In this regard, the medical devices industry has played an important role in crisis management and providing healthcare and has faced several major challenges in supplying raw materials, production activities, and distribution activities due to the disruptions caused by the pandemic. One of the critically important issues in the medical devices supply chain is supplier selection. Hence, this research investigates the supplier selection problem considering the emerging concepts that have dramatically attracted the attention of researchers after the COVID-19 pandemic, namely viability and Industry 5.0.

In this study, a hybrid fuzzy decision-making approach is developed to investigate the viable supplier selection problem considering the Industry 5.0 dimensions. In this regard, in the first stage, according to the literature and experts, the main indicators of the research problem are extracted, and their weights are calculated using the fuzzy best-worst method. In the next stage, the feasible suppliers are evaluated by employing the fuzzy VIKOR method. Also, to show the robustness and validation of the proposed approach, its results are compared with those of traditional approaches.

In this study, a list of indicators, including six aspects and 34 criteria, is provided for the research problem based on its nature, and their importance has been computed. Based on the outputs, the general metric is the most important aspect, and the human-centricity metric is the least significant. Also, the results show that in addition to the general criteria, such as cost and quality, other criteria, such as reliability, technical capability, pollution control, risk reduction, and service, also play a significant role in the process of selecting suppliers. The results indicate that managers in today's competitive and industrial markets should redirect their attention from traditional criteria to those contributing to the sustainability and improvement of their systems' performance.

 Reading the results of this research can help Industrial and organizational managers evaluate the potential suppliers of their companies based on the viability and Industry 5.0 dimensions and select the best ones, which can significantly improve the performance and efficiency of their businesses.

Uncertainty is a common occurrence in real-world issues that often make decision-making difficult. Specifically, when it comes to managing a supply chain, the decision of which supplier to choose is complicated by a lack of information and knowledge, which leads to different levels of uncertainty in the attributes and alternatives, making it hard to make the right decision. In this article, a multi attribute decision-making method within a qualitative reasoning framework, where the assessment of problem attributes is carried out using different backgrounds and levels of experts' knowledge, is presented, and the score of the alternatives by evaluation a K-dimensional vector of qualitative labels is determined. To achieve it, the qualitative reasoning framework is first described, and then the proposed method in the same framework is described. The validity of the proposed method was verified by two practical examples. An example demonstrated the effectiveness of the proposed model and the results were compared with other methods. Finally, a real example was employed to select the best supplier. The conditions for the practical example are chosen in such a way, that it cannot be solved by using the previous methods. The results of this study explain the advantage of using multiscale linguistic space over other linguistic methods and also by analyzing two practical examples, the validity of the proposed method and its advantage over other methods in the qualitative reasoning space is confirmed.

In today's competitive world, supply management plays a significant role in achieving an efficient supply chain. One of the most important goals of supply management is to select sustainable suppliers and determine the optimal order allocated to suppliers. The process of selecting a sustainable supply begins with the determination of the criteria which are effective on the decision. Considering that the importance of all these criteria is not the same for organizations, multi-criteria decision-making methods are used to determine the weights of these critera. In this paper, three methods of Fuzzy DEMATEL, combination of analytical network process method and fuzzy DEMATEL type 1 and combination of analytic network process method and Fuzzy DEMATEL type 2 are used to determine the weights of effective criteria. Also, to determine the scores of suppliers, the innovative combined approach of fuzzy Taguchi loss function and fuzzy method of similarity to the ideal solution is used. In the hybrid approach, first, experts give scores to suppliers for their performance in different political, economic, social conditions, and based on this, the fuzzy Taguchi loss function is calculated. Considering that the loss function has a negative charge, the Taguchi loss functions are inverted and used as the input of the fuzzy TOPSIS method. In this paper, the sensitivity of the mentioned multi-criteria decision-making methods in calculating the weights of the criteria is examined with different conditions. The scores of suppliers are calculated based on their performances in the worst, normal and best conditions.

Supplier selection and determining appropriate replenishment policies is one of the major concerns in production systems and supply chains. This paper describes the supply chain of integrated buyers and suppliers of perishable product. The retailer supplies the product it needs from different manufacturers. Products purchased by manufacturers are perishable products, and their Perishable rate is expressed as a fixed percentage of retailers' and manufacturers' inventories. In this situation, the selection of suppliers and the determination of the quantity to purchase from each supplier have a great impact on the optimization of the supply chain. Based on the fixed demand of the end customers, the retailer tries to determine its optimal replenishment policy, and based on this optimal policy, the process of purchasing raw materials from manufacturers, as well as the time and amount of purchase from each manufacturer will be determined. Among these, the supplier that can deliver the product within the specified time and at the lowest cost will be selected. The main purpose of this paper is to select suppliers and determine replenishment policies in a way that minimizes the total cost of this chain of supply, including retailer and supplier costs. This model uses a mixed-integer linear programming approach. Finally, this model was checked with a numerical example.

Material Requirements Planning (MRP) is a priority planning method that calculates the materials needed to meet the demand for all products and parts in one or more parts of the factory. Because choosing the right supplier for the organization brings significant savings, the most important activity of the buying operation is choosing the right supplier. The aim of this study is to design an extended inventory model to identify and Supplier Selection and Material Requirements Planning in the supply chain. For this purpose, an inventory system including the main parameters of initial inventory level, defect rate and decision when supply shortage was designed. Then the distribution model was designed for the relationship between the inventories of supply chain units and distributors. After modeling the demand for each supply chain unit, the inventory model was performed to Material Requirements Planning and Supplier Selection based on dynamic simulation for the supply chain. Material Requirements Planning was then sensitized based on changes in demand and changes in production capacity and changes in inventory and finally suppliers were selected. The results showed that with increasing demand, the cost of new raw materials also increases. Also, at 80% of the base production capacity, the Material Requirements Planning is unworkable and is not able to meet the basic demand. Reduced capacity leads to high inventory costs. With 110 and 120% of base capacity, there was a reduction in production costs. Also, with high initial inventory, a decrease in total costs was observed, and in 120% of the basic initial inventory, although inventory costs increased, the cost of new raw materials decreased significantly. Also, the sensitivity for selecting a supplier to the fixed cost parameter of ordering from the supplier is less than other cost parameters

Introducing new products for companies in a competitive business environment is imperative. Designing an appropriate supply chain for the successful development of new products leads to growth and success in the competition. Supply chain design or configuration is essential to the success of a business since it can increase the profit of the whole supply chain. Supply chain management aims to determine the link between network components and specify the inventory level in each part of the supply network, production quantity, manner of transportation, and other related problems. Also, during the new product development process, companies encounter decisions such as producing independent products, immediate replacement of a new product with an old one (single-product rollover strategy), or gradual replacement over several periods (dual-product rollover strategy). A dual-product rollover strategy can be more efficient and less costly in some cases, although it has received less attention. In the present study, the four-level supply chain (including suppliers, manufacturers, distributors, and customers groups) model for old and new products is presented by considering a dual-product rollover strategy. Objective function consists of net profit for manufacturers and distributors, cost of customer dissatisfaction, cost of unemployment resources, and cost of designing new products. Also, constraints control the equality between production and inventory with the flow of products, production capacity, product rollover strategy, shipping the goods after that connection determined, and level of initial inventory. The model is solved by GAMS software using actual data from a company that is active in the digital appliance industry and produces wired and wireless headphones as non-independent products (it is implied that with launching the wireless headphone, demand for wired headphones is reduced). After presenting the results, sensitivity analysis is performed on the parameters to determine the most effective ones on the objective function. Then, the results of solving this model under a dual-product rollover strategy are compared with those of the single-product rollover strategy (the model can be converted into a single-product rollover strategy by modifying rollover parameter), and managerial insights are presented.