The Inventory Control System of Reverse Logistics for E-Commerce Packaging Recovery Based on BP Neural Network

The paper combines BP neural network to optimize the control system of e-commerce packaging and reverse logistics inventory. Through improving the hardware configuration structure of the system, the system can be improved and the operation effect of the system can be improved. The software flow and operation algorithm of the storage control system of e-commerce packaging recycling reverse logistics are optimized step by step, and the logistics is delivered by following the vehicle on the spot and visiting the logistics The distribution personnel collect the relevant data and data in the process of logistics and transportation, draw the reverse logistics business flow chart, point out the situation of reverse logistics before and after the goods distribution and distribution due to the cancellation of orders or transactions by customers, and the application for return of goods after the transaction. Meanwhile, it points out that the sales return operation site in the reverse logistics management process is chaotic and not formed the clear business process specification and other problems can effectively control the reverse logistics inventory of e-commerce packaging recovery. Finally, the experiment proves that the e-commerce packaging recycling reverse logistics inventory control system is more practical in the practical application process, and fully meets the research requirements.

Analysis Control Of Inventory Of Non Subsidy Fertilizer Merchandise With Economic Order Quantity (EOQ) Method In CV. Dohar Agro Mandiri

Economic Order Quantity (EOQ) is a mathematical model that determines the number of items that must be ordered to meet the projected demand, with minimized inventory costs. The types of costs to run the business cycle are storage costs and ordering costs. The purpose of this research is to analyze "Analysis of Non-Subsidized Fertilizer Inventory Control with Economic Order Quantity (EOQ) Method at CV. Dohar Agro Mandiri. The total inventory obtained using the EOQ method is 11,003 with a purchase frequency of 3 times. Using the EOQ method the company must reorder when the merchandise inventory is 1,015 zak, with the EOQ method the maximum inventory that the company must maintain is 12,018 per day. The total inventory cost of fertilizer merchandise inventory is 24,648. In other words, inventory control using the EOQ method can help companies achieve an optimal level of inventory ordering and ordering frequency.

Simulation optimization of an inventory control model for a reverse logistics system

Nowadays, companies are recognizing their primordial roles and responsibilities towards the protection of the environment and save the natural resources. They are focusing on some contemporary activities such as Reverse Logistics which is economically and environmentally viable. However, the integration of such an initiative needs flows restructuring and supply chain management in order to increase sustainability and maximize profits. Under this background, this paper addresses an inventory control model for a reverse logistics system that deals with two separated types of demand, for new products and remanufactured products, with different selling prices. The model consists of a single shared machine between production and remanufacturing operations, while the machine is subject to random failures and repairs. Three stock points respectively for returns, new products and remanufactured products are investigated. Meanwhile, in this paper, a modeling of the problem with Discrete-Event simulation using Arena® was conducted. Regarding the purpose of finding, a near-optimal inventory control policy that minimizes the total cost, an optimization of the model based on Tabu Search and Genetic Algorithms was established. Computational examples and sensitivity analysis were performed in order to compare the results and the robustness of each proposed algorithm. Then the results of the two methods were compared with those of OptQuest® optimization tool.

Optimization of Raw Material Inventory Control CV. Dirga Eggtray Pinrang Using Probabilistic Model with Backorder and Lostsales Condition

This research discusses about the comparison of raw material inventory control CV. Dirga Eggtray Pinrang. It starts with forecasting inventory for the next 12 periods using variations of the time series forecasting method, where the linear regression method provides accurate forecasting results with a Mean Absolute Percentage Error (MAPE) value of 1,9371%. The probabilistic models of inventory control used are the simple probabilistic model, Continuous Review System (CRS) model, and Periodic Review System (PRS) model. The CRS model with backorder condition is a model that provides the minimum cost of Rp. 969.273.706,20 per year compared to another probabilistic model with the largest difference of Rp. 1.291.814,95 per year, with the optimum number of order kg, reorder level kg, and safety stock kg.