Analisis Perbandingan Persediaan Optimum dengan Metode Lot for Lot, Period Order Quantity dan Economic Part Period

PT. X is a company engaged in the production of electrical and electronic equipment, one of its products is camera. This research aims to compare the inventory policies that have been implemented by the company with other dynamic deterministic models. In the production process, the company uses a stock policy with the Lot for Lot (LFL) method, but the total costs incurred by the company and the frequency of ordering are still quite high. This research aims to compare the inventory policies that have been implemented by the company with other dynamic deterministic models, such as Period Order Quantity (POQ) and Economic Part Period (EPP) methods so that the optimal inventory method can be determined. The results of this study indicate that the Economic Part Period (EPP) is the optimal method with a total cost of Rp. 69,284,600 and the order frequency is 7 times.

Joint Pricing and Inventory Policies for Perishable Items with Price Discount based on Freshness Index

It is generally observed that the products losses its freshness with the course of time that stimulates depression in demand of the product. In these circumstances, price discounts are necessary to raise the market. This is why, when the product's the index of freshness reaches a certain level, we created an inventory model wherein price reductions are provided at a sale price. The main goal is to figure out what the best selling price and cycle time are in order to maximise profit. The meaning and uniqueness of an ideal model solution are incorporated into the circumstances. The next move is to use a simple algorithm to find an optimal solution. Finally, a numerical example is presented, followed by a sensitivity analysis.

Determinant Factors Affecting Performance of Supply Chain in Pulp and Paper Industries During Pandemic Era in Indonesia

One of the important keys for businesses today to be able to compete is to strengthen their supply chain management system.The impact of a pandemic is felt by all types of businesses, the most important unit of business that also feels the impact of the pandemic is how businesses maintain and even improve the performance of their supply chain management and one of the businesses or industries that is sufficiently affected by the pandemic for its supply chain resilience ispulp and paperindustry. The purpose of this study is to improve the performance of the supply chain, especially in the pulp and paper industry in Indonesia during the pandemic. This study uses two independent variables, namely inventory policies and information sharing and one dependent variable, namely supply chain performance. Data collection in the form of a survey using questionnaire media was carried out on 85 practitioners who work in supply chain units such as production, marketing and logistics. Data collection was carried out from July to September 2020. The results of this study are the conclusion that there is a positive and significant effect of inventory policies and information sharing on supply chain performance. The estimated coefficient of inventory policy on supply chain performance is 0.61, while the estimated coefficient of information sharing on supply chain performance is 0.24. The simultaneously effect of the two independent variables on the dependent is 0.72.

Simulation analysis of initial inventory in BSSs

Purpose This paper aims to propose an alternate, efficient and scalable modeling framework to simulate large-scale bike-sharing systems using discrete-event simulation. This study uses this model to evaluate several initial bike inventory policies inspired by the operation of the bike-sharing system in Mexico City, which is one of the largest around the world. The model captures the heterogeneous demand (in time and space) and this paper analyzes the trade-offs between the performance to take and return bikes. This study also includes a simulation-optimization algorithm to determine the initial inventory and present a method to deal with the bias caused by dynamic rebalancing on observed demand. Design/methodology/approach This paper is based on the analysis of an alternate and efficient discrete-event simulation modeling framework. This framework captures the heterogeneity of demand and allows one to experiment with large-scale models. This study uses this model to test several initial bike inventory policies and also combined them with an optimization engine. The results, provide valuable insights not only for the particular system that motivated the study but also for the administrators of any bike-sharing system. Findings The findings of this paper include: most of the best policies use a ratio of bikes: docks near to 1:2; however, it is important the way they are initially allocated; a policy that contradicts the demand profile of the stations can lead to poor performance, regardless the quick and dynamic changes of bike locations during the morning period; the proposed simulation-optimization algorithm achieves the best results. Research limitations/implications The findings are limited to the initial inventory of the system under study. The model assumes a homogeneous probability distribution function for the travel time. This assumption seems reasonable for the system under study. This paper limits the tested inventory policies to simple practical rules. There might be other sophisticated methods to obtain better solutions, but they might be system-specific. Practical implications The insights of this paper are valuable for operators of bike-sharing systems because this study focuses on the analysis of the impact of the initial inventory assuming that dynamic rebalancing may not be existing during the morning peak-time. This paper finds that initial inventory has a great impact on the performance, regardless of how quickly the bikes are dispersed across the system. This study also provides insights into the effect of dynamic rebalancing on observed demand. Social implications Increasing knowledge about the operation of the bike-sharing system has a positive effect on society because more cities around the world could consider implementing these systems as a public transportation mode. Furthermore, delivering suggestions on how to increase the user service level could incentivize people to adopt bikes as a mobility option, which would contribute to improve their health and also reduce air pollution caused by motorized vehicles. Originality/value This paper considers that the contributions of this work to existing literature are the following: this study proposes a novel efficient and scalable simulation framework to evaluate initial bike inventory policies; the analysis presented in the paper includes an approach to deal with the bias in the observed demand caused by dynamic rebalancing and the analysis includes the value of demand information to determine an effective initial bike inventory policy.