A simulation model for a continuous review inventory policy for healthcare systems

Impact of inventory management on demand fulfilment, cost and emission of forest-based biomass supply chains using simulation modelling

This paper is dedicated to modeling and performances analysis of inventory systems using BDSPN, a stochastic Petri net model capable of describing essential characteristics of logistical systems (batch behaviors, randomness, operational policies, synchronization of various flows). In this paper, an analytic method based on the Markov regenerative theory introduced by Choi for a particular class of stochastic Petri nets is presented and applied to our model. An inventory system with (batch) stochastic demand; constant replenishment lead time and continuous review (s, S) policy is modeled and its performances are evaluated using the analytic method

This paper analyzes the use of a constant critical level policy for fast-moving items, where rationing is used to provide differentiated service levels to two demand classes (high priority and low priority). The previous work on critical level models, with either a continuous or periodic review policy, has only considered slow-moving items with Poisson demand. In this work, we consider a continuous review (Q, r, C) policy with two demand classes that are modeled through continuous distributions, and the service levels are measured by the probability of satisfying the entire demand of each class during the lead time. We formulate a service level problem as an non-linear problem with chance constraints for which we optimally solve a relaxation obtaining a closed-form solution that can be computed easily. For instances, we tested, computational results show that our solution approach provides good-quality solutions that are on average $$0.3~\%$$0.3% from the optimal solution.

The replenishment policy of agri-products with stochastic demand in integrated agricultural supply chains

Background: The high number of purchases created various impacts. It delayed other activities of RMSc CB operations. Inventory management staff had to spend most of working time for the procurement of supplies. This time constraint had affected the inventory control. In 2001, RMSc CB applied for the ISO/IEC 17025 accreditation. The nonconformance to the quality assurance system was found in the area of inventory management particularly in inventory control. The inventory scientific equipment control involve keeping detailed record on each piece of equipment, including such information were serial numbers, date the equipment was purchased, price, location, agency etc. The control and maintenance of scientific equipment supplies according to the quality assurance system had not been in place. The actual coding numbers labeled on scientific equipment were still the old numbers that were not matched with the number in the record of durable articles developed in 2001. Some equipment had not even been labeled with any numbers at all. This was not compliant to the quality assurance inventory control according to SENAC system (Scientific Equipment Name and Coding number system). The high number of purchases created various impacts. It delayed other activities of RMSc CB operations Inventory Staff had to spend most of working time for the procurement of supplies. This time constraint had affected the inventory control. Scientific equipment had not been controlled by SENAC system of the quality assurance system. This problem presented during 1999-2001 but no actions were done. According to the RMSc CB’s Vision in 2005, laboratory analysis should apply for ISO/IEC 17025 accreditation, Non-conformances have been found every time of the inspection for ISO/IEC 17025 accreditation of RMSc CB. More importantly, it had caused problems. Therefore, these problems had to be addressed as an urgent basis. This was based on the concept of work model according to “Open System Theory” of Robbins and Coulter, 1999, So that the working team was established to address the problems. They conduced a study in effort to find solution using SWOT analysis and solving problem. Objective: The goal of the project is to enhance the effectiveness of inventory management system of RMSc CB through the development of inventory procurement; inventory control; and improvement of related staff performance in order to achieve the following objectives. Methods: The project was implemented during 6 month consisting of 3 phases. The first phase focuses on preparation by reviewing existent inventory management system, planning and goal setting ,and design and developing supply and inventory management system. During the second phase the inventory staff’s had been trained and new system was tested. The last phase was an evaluation. Data were collected using both qualitative and qualitative methods including the use of survey, observation and in depth interviews. Results: The study found that the knowledge and skill of inventory staff have increased. The drop of annual number of the office supply purchase in 2003 reached the target of decreased of 50 percentage. And the coding numbers of all scientific equipment were matched and update with the ones in the inventory control system. The satisfaction levels of RMSc CB staff have increased as well. Conclusion: The project was successful in implementation. The evaluation program provided information about the results of the training in term’s knowledge and skills of inventory staff have increased. New inventory systems management could be decrease frequency purchase office supplies and error scientific equipment coding number. That could ultimately enhance staff’s satisfaction. However the overall program performance could be further improved.

In this paper, an incentive scheme based on crashing lead time is proposed to coordinate a supplier-retailer supply chain (SC). In the investigated SC, the supplier applies a lot-for-lot replenishment policy to replenish its stock and determines the replenishment multiplier. Moreover, the transportation lead time is considered under the control of the supplier. The retailer as downstream member manages his inventory system according to the periodic review replenishment system (R, T). The review period (T) and order-up-to level (R) decisions along with the retail price are simultaneously optimized by the retailer. These decisions are made by the retailer influence the profitability of SC as well as the supplier's profitability. The investigated SC is modeled under three different decision making structures, i.e., (1) decentralized decision making model, (2) centralized decision making model, and (3) coordinated decision making model. By developing a lead time reduction policy as an incentive strategy, the pricing and periodic review replenishment decisions are coordinated. In the proposed incentive approach, the supplier by spending more cost and changing a fast transportation mode aims to crash the lead time in order to entice the retailer to accept the joint decision making strategy. In the suggested incentive scheme, two transportation modes (one slow and one fast) are supposed. Further, maximum and minimum lead time reduction, which are acceptable for both members, are determined. Moreover, a set of numerical examples along with a real case are carried out to demonstrate the performance and applicability of the developed models. The results demonstrate that the proposed incentive strategy is able to achieve channel coordination. Moreover, the results show the applicability of the developed coordination model under the high demand uncertainty. In addition, the proposed coordination model will fairly share the obtained profits between two SC members.

Chemical inventory management system has been experiencing a new revolution from traditional inventory system which is manual to an automated inventory management system. In this paper, some review of the classic and modern approaches to chemical inventory management system has been discussed. This paper also describe about both type of inventory management. After a comparative analysis of the traditional method and automated method, it can be said that both methods have some distinctive characteristics. Moreover, the automated inventory management method has higher accuracy of calculation because the calculations are handled by software, eliminating possible errors and saving time. The automated inventory system also allows users and administrators to track the availability, location and consumption of chemicals. The study of this paper can provide forceful review analysis support for the chemical inventory management related research.

Research on inventory models has been conducted intensively, including the model for stochastic demand. However, inventory models for stochastic demand are not easy to solve using an exact algorithm. In this paper, we develop a Monte Carlo simulation method to solve inventory problems with stochastic and intermittent demand. Simulation is conducted to evaluate continuous and periodic review policies. The simulation models are optimized using the evolutionary algorithm. The models are applied to data from one bicycle shop in Indonesia for five different items. The result shows that the economic order quantity ( R,Q ) policy is better than the ( s,S ) policy for two items and it is better than the ( S,T ) policy for three items.

In today’s fast-paced and competitive market place, organizations need every edge available to them to ensure success in planning and managing inventory of items with demand uncertainty. In such an effort, cost effective methods in determining optimal replenishment policies are paramount. In this paper, a mathematical model is proposed that optimize inventory replenishment policies of a periodic review inventory system under stochastic demand; with particular focus on malaria drugs in Ugandan pharmacies. Adopting a Markov decision process approach, the states of a Markov chain represent possible states of demand for drugs that treat malaria. Using weekly equal intervals, the decisions of whether or not to replenish additional units of drugs were made using discrete time Markov chains and dynamic programming over a finite period planning horizon. Empirical data was collected from two pharmacies in Uganda. The customer transactions of drugs were taken on a weekly basis; where data collected was analyzed and tested to establish the optimal replenishment policy and inventory costs of drugs. Results from the study indicated the existence of an optimal state-dependent replenishment policy and inventory costs of drugs at the respective pharmacies.

Reducing emissions in transportation and inventory management: (R, Q) Policy with considerations of carbon reduction

This paper aims at comparing and verifying the effectiveness of existing (r, Q) inventory systems for perishables with fixed lead time and lifetime. The total inventory operating costs are compared to measure the performance for each policy in order to choose the best one that leads to the lowest cost. We show that, under backordered demand, the (r, Q) policy obtained from [8] deviates on average by less than one percent from the optimal (r, Q) policy and performs better than a previous model developed by Chiu [2] when Q ≥ r. When excess demand are lost, Chiu's model [2] performs better than the model of [8]. But both models are unsuitable when the ordering cost K increases. Keywords: Perishable products, Inventory control, Continuous review policy.

Inventory management is the main task of an organization to reach its objective of maintaining the number of stocks precisely and minimizing waste. Web-based inventory management in a university environment is expected to help the employees in keeping up with innovations on the status of tools and equipment. It is only fitting that inventory data management is also capable of accommodating distance. The use of the internet by using mobile computing which automatically can do tagging of inventories including information about the coordinate will broaden the potential of database using mobile computing technology with wireless data communication aided with 2D-barcode decoding automatization makes it possible to synchronize (record and track) on-line to the central database using some computers that work simultaneously and directly from the field. This inventory system can synchronize data directly from the field and the information can simultaneously be accessed by the users. Mobile computing (android Smartphone, computer tablet) is used as a mobile station that is capable of decoding the tags of inventories and buildings (in the 2D-barcode) and associating automatically with the database wireless networks and the internet to eliminate the distance factor and overhead-process (pre-processing of data from the field to the data storing station).

Inventory management can be considered as one of the main components of planning and production control. In the literature numerous mathematical models are presented for inventory management, which approach different aspects related to this management. The development of efficient inventory models and the adoption of appropriate optimization methods for solving these models are needed to support in making decisions to inventory management. In this paper, we propose an inventory model that works with multiple products and multiple resource constraints, deciding between the continuous review and periodic review systems. This model is formulated as a nonlinear mixed integer optimization problem. It explores for the resolution of this model, an approach based on Branch-and-Bound method and interior point method. In order to propose this model and choose the method for its resolution, initially an investigation in the literature review on the topic is done. Then, the concept of continuous review and periodic review systems is explored. Finally, two computational tests are proposed, one to compare the results of proposed nonlinear model with the linear model and the other to verify its efficiency and applicability. The results show the potential of the model and solution method used to work with inventory system.

This paper studies a buyer sourcing a product from multiple suppliers under stochastic demand. The buyer uses a (Q, s) continuous review, reorder point, order quantity inventory control system to determine the size and timing of orders. Lead time is assumed to be deterministic and to vary linearly with the lot size, wherefore lead time and the associated stockout risk may be influenced by varying the lot size and the number of contracted suppliers. This paper presents mathematical models for a multiple supplier single buyer integrated inventory problem with stochastic demand and variable lead time and studies the impact of the delivery structure on the risk of incurring a stockout during lead time.

In recent years, the correct management of inventories has become a fundamental pillar for achieving success in enterprises. Unfortunately, studies suggesting the investment and adoption of advanced inventory management and control systems are not easy to find. In this context, this article aims to analyze and present an extensive literature concerning inventory management, containing multiple definitions and fundamental concepts for the retail sector. A systematic literature review was carried out to determine the main trends and indicators of inventory management in Small and Medium-sized Enterprises (SMEs). This research covers five years, between 2015 and 2019, focusing specifically on the retail sector. The primary outcomes of this study are the leading inventory management systems and models, the Key Performance Indicators (KPIs) for their correct management, and the benefits and challenges for choosing or adopting an efficient inventory control and management system. Findings indicate that SMEs do not invest resources in sophisticated systems; instead, a simple Enterprise Resource Planning (ERP) system or even programs such as Excel or manual inventories are mainly used.