multiple-criteria decision-making
Sara Asili; Ebrahim Teimoury
Abstract
Considering the competitive environment between suppliers, the issue of choosing them based on important criteria is very important for decision makers, especially in the LARS supply chain, which is a combination of sustainable and LARG supply chains. The aim of this paper is to present a multi-objective ...
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Considering the competitive environment between suppliers, the issue of choosing them based on important criteria is very important for decision makers, especially in the LARS supply chain, which is a combination of sustainable and LARG supply chains. The aim of this paper is to present a multi-objective mathematical model for selecting suppliers based on criteria related to the LARS supply chain concepts. The innovations of the presented model include simultaneous consideration of multiple objectives, multiple periods, multiple products, and master production schedule. The quality of the presented model has been examined on a case study in the country's automotive industry. In this paper, at first, the most important criteria have been extracted from the literature, then finalized by experts in the country's automotive industry, and DEMATEL approach has been used to examine the internal relationships of the criteria in each category of criteria. Secondly, the network of criteria is determined, the importance of each criterion relative to the others was determined using a pairwise comparison matrix and considered as input to the Super Decision software. At last, a mathematical model for optimal supplier selection is presented. Based on the results obtained, the ordering cost had the greatest impact on the objective function. Also, considering the concept of backlog demand has led to flexibility in production volume and, as a result, reduced overall costs.IntroductionLARG Supply Chain Management represents an integrated approach that combines lean, agile, resilient, and green paradigms in supplier relationship management. This holistic framework enables organizations to simultaneously leverage the advantages of each approach while compensating for their inherent limitations. For example, lean supply chain management focuses on minimizing inventory levels to reduce waste and cost; agile supply chain management emphasizes responsiveness and flexibility to meet dynamic market demands; resilient supply chain management enhances the ability to withstand and recover from disruptions; and green supply chain management aims to minimize environmental impacts and promote sustainability. According to Babaei et al. (2017), in an increasingly volatile and uncertain global environment, organizations are placing greater emphasis on supply chain resilience as a key capability for survival and competitiveness. Resilient supply chains are characterized by their capacity to absorb shocks and maintain operational continuity. Meanwhile, the concept of sustainable supply chain management—which addresses environmental, social, and economic concerns—has attracted growing interest among both academics and practitioners. More recently, researchers have begun to explore the LARS framework as a comprehensive model that overlaps with sustainability initiatives, particularly through its emphasis on green practices. However, despite their similarities, LARS and sustainability are distinct in scope and application. This study aims to identify a comprehensive set of criteria for supplier selection under the LARS framework, thereby supporting more informed and strategic decision-making in supply chain management. To this end, relevant criteria will be extracted through expert input from a leading firm in the Iranian automotive industry. In parallel, an extensive literature review will be conducted to incorporate practical and validated indicators associated with lean, agile, resilient, and sustainable supply chain practices. A Likert-scale-based questionnaire will be developed to assess suppliers against these criteria, and the resulting scores will serve as input for a multi-objective mathematical model.The remainder of this paper is structured as follows: Section 2 presents a review of the relevant literature. Section 3 introduces the proposed mathematical model. Section 4 details the case study and analyzes the results. Finally, Section 5 concludes the paper with key findings and managerial implications.MethodsIn this study, the most critical criteria were initially extracted through a thorough review of the existing literature and subsequently refined based on expert insights from the Iranian automotive industry, with a case study focused on Zamiad Company. To analyze the interrelationships among the criteria within each category, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was employed. Following the identification of the criteria interaction network, the relative importance of each criterion with respect to the others was determined using pairwise comparison matrices. These comparisons served as input data for the Super Decisions software, facilitating the application of the Analytic Network Process (ANP). In the next phase of the study, a mathematical model was developed to support the optimal selection of suppliers.Discussion and resultsIn this research, the required data for all ten products were collected from the internal information systems of Zamiad Company. All collected data were evaluated in terms of consistency ratio, which was confirmed as being below 0.1, ensuring the reliability of the pairwise comparisons. After entering the data into Super Decisions software, the output—including the weights of each supplier for each product—were obtained. The results were reviewed and validated by experts at Zamiad Company.Although the proposed model is inherently nonlinear, it was linearized to reduce computational complexity. This adjustment significantly decreased the solution time, which is crucial when solving large-scale problems.The developed mathematical model aims to optimize the selection of suppliers for each product in each production period and to determine the allocated quantity to each supplier. The model incorporates various cost factors, including production, ordering, inventory holding, product shortage, and supplier switching costs. While the parameters of the model were intended to reflect actual company data, due to the confidentiality policies of Zamiad Company, some parameters were not accessible to the researchers. Therefore, these values were generated using normal distributions within predefined intervals based on expert judgment.The model was implemented over two six-month production periods, in alignment with Zamiad’s typical contractual arrangements with its suppliers. Based on the obtained results, ordering cost had the greatest impact on the objective function. Moreover, considering the concept of backlog demand has introduced flexibility in production volume, thereby reducing the overall costs.ConclusionThis study aimed to identify key criteria affecting supplier selection and to determine their relative importance within the integrated LARS supply chain approach. Based on the obtained results, incorporating the production planning process reduces the diversity of suppliers across different periods. This can be attributed to production integration and the model’s preference for maintaining existing contracts over frequent changes. Given the current economic conditions in the production environment, it is essential to consider all relevant parameters in the supplier selection process simultaneously. The findings indicate that accounting for production planning within the LARS framework leads to more effective supplier selection. Among the evaluated parameters, production cost and product ordering cost had a greater impact on the overall performance of the proposed model compared to other factors. Therefore, managerial strategies should focus on controlling these key cost components. This research has contributed by identifying and evaluating these critical parameters.
Seyed Mohammad Taghi Fatemi Ghomi; Ehsan Arabzadeh; Behrooz Karimi
Abstract
Home health care services have a key importance in modern societies. Most organizations working in this area in Iran use the traditional procedure to plan and manage medical staff and determine the arrangement of visiting patients. This procedure often increases costs and reduces the satisfaction of ...
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Home health care services have a key importance in modern societies. Most organizations working in this area in Iran use the traditional procedure to plan and manage medical staff and determine the arrangement of visiting patients. This procedure often increases costs and reduces the satisfaction of patients. In this paper, a multi-period routing and scheduling model is proposed in order to visit patients and provide them medical services. Considering both dependency and independence of a patient's visits with each other, assuming the model as multi-depot as well as multi period are some innovations of this study. The main purpose of the proposed model is to reduce total costs of home health care organization. Model has been solved in small scale by GAMS software. To solve the model in large scale, developed Variable neighborhood search is proposed and compared with simulated annealing algorithm and ant colony system. Results show that costs are decreased and the proposed algorithm has better performance
