Pengembangan Model Persediaan Produk Perishable dengan Pertimbangan Dynamic Pricing

Produk perishable adalah produk yang nilainya berkurang seiring berjalannya waktu. Pengelolaan persediaan produk perishable menjadi tantangan yang dialami oleh retailer. Permasalahan muncul ketika biaya persediaan meningkat akibat banyaknya produk terbuang atau waste. Tujuan dari penelitian adalah maksimasi profit dengan memberikan rekomendasi kebijakan pengadaan persediaan di bawah dynamic pricing. Fokus optimasi penelitian ini adalah menentukan lot size dan reorder level optimal. Penyelesaian masalah adalah menggunakan model simulasi dengan mempertimbangkan perubahan harga produk seiring menurunnya kualitas produk. Metode simulasi dalam penelitian ini adalah discrete event simulation dengan menggunakan software simulasi. Event dalam simulasi persediaan ini meliputi pelayanan permintaan dan penambahan persediaan. Kebijakan replenishment dalam penelitian ini adalah continuous reviews. Skenario terbaik didapatkan dari kombinasi lot size dan reorder level optimum. Model simulasi persediaan dibangkitkan berdasarkan data persediaan buah di salah satu retailer besar di Indonesia. ================================================================================================================================ Perishable products are products whose value decreases over time. Inventory management for perishable products is a challenge experienced by retailers. Problems arise when inventory costs increase due to the large amount of wasted or waste products. The aim of this research is to maximize profit by providing policy recommendations for inventory procurement under dynamic pricing. The focus of this research optimization is to determine the optimal lot size and reorder level. To solve this problem a simulation model is created by considering changes in product prices as product quality decreases. The simulation method in this study is a discrete event simulation using simulation software. Events in this inventory simulation include the arrival of customers and the addition or reduction of inventory levels. The replenishment policy in this study is continuous reviews. Simulation scenarios were generated to obtain an optimum lot size and reorder level. The best scenario is obtained from a combination of optimum lot size and reorder level. An inventory simulation model was generated based on fruit inventory data at one of the major retailers in Indonesia