A decision support system for supplier selection and integrated closed-loop supply chain network design problems

In today's business environment, organizations must adopt an effective supply chain management strategy to survive and succeed in a competitive market. Two critical factors in developing an effective strategy are a well-planned closed-loop supply chain network design and the selection of suitable suppliers that meet the criteria of the business. A closed-loop supply chain is an approach that optimizes network decisions by carefully managing materials, cash, and information, considering recycling and reuse processes within the organization. Supplier selection is a critical decision-making process that enables businesses to choose suitable suppliers for sourcing raw materials, goods, and services while considering competitive advantage. Closed-loop supply chain and supplier selection are essential for organizations to achieve fundamental goals such as sustainability, cost-effectiveness, quality assurance, and customer satisfaction. This thesis will be a step towards understanding, analyzing, and solving closed-loop supply chain and supplier selection problems. The study will give businesses a strategic perspective in these areas and help improve their decision-making processes to gain a competitive advantage. The study aims to propose a closed-loop network design model that considers product perishability, starting with LARG (lean, agile, resilient, and green) supplier selection in a process affected by the COVID-19 pandemic. The criteria considered for supplier selection include traditional, social, LARG-focused, and pandemic-specific criteria, determined by reviewing relevant literature. The obtained criteria are used to construct a criterion weighting process using Intuitionistic Fuzzy Set Theory (IFS) and Full Consistency Methods (FUCOM). The weighting process considers evaluations from different experts and determines criterion weights using a mathematical modeling approach. To evaluate suppliers and obtain the supplier scores, which are a parameter to be considered in the proposed mathematical model, the applicability of the Complex Proportional Assessment (COPRAS) Method is presented in the study. The study proposes a closed-loop supply chain network design model that considers sustainability for a perishable product. Under the influence of supply uncertainty during the pandemic, the Probabilistic-Mixed Integer Linear Programming Model is proposed in the study. The research part of the proposed mathematical model focuses on the healthcare sector and observes network design through a hospital operating in Turkey. Sensitivity analysis is performed on supplier scores, shelf life, and supplier capacity parameters in the solutions. The IBM ILOG CPLEX 20.1.0 program is used to solve the case. The obtained solutions highlight the importance of supplier selection in closed-loop supply chain network design for a perishable product and demonstrate the possibility of optimal inventory tracking.