Integrating Social Costs Into Joint Economic Lot Sizing: Optimizing Order Quantity To Minimize Inventory And Mental Health-related Costs In A Multi-buyer Batik Supply Chain

Abstract

This research aims to develop an integrated model for optimizing order quantities within the batik supply chain, combining economic cost reduction with mental health considerations of the workforce. The study applies the Joint Economic Lot Size (JELS) model to minimize inventory costs (holding, ordering, and lost sales), while also addressing social costs, particularly the mental health challenges faced by workers in batik production. The focus is on balancing production efficiency and employee welfare by integrating mental health data (e.g., stress, burnout, and workload) into the traditional economic models. Data from a batik vendor in Yogyakarta serving multiple retailers was collected through surveys, interviews, and historical data, evaluating the impact of mental health on productivity and overall supply chain performance. The research incorporates evolutionary algorithms to optimize order cycles, reduce the Grand Total Cost (GTC), and improve both economic and social sustainability. The findings indicate that optimizing order quantities while considering worker mental health can significantly reduce operational costs, enhance employee well-being, and improve supply chain efficiency. This research provides valuable insights for industries, especially labor-intensive ones like batik, to adopt more sustainable and humane supply chain practices.