Distribution Inventory System Research Articles

Sustainable supply chain planning with the flexible provisions of inter-period emission credits borrowing and banking under a multi-period carbon trading scheme

Although the carbon emission trading regulation proves its advantage of reducing abatement costs, the timing of operating activities makes overage or shortage of allocated emission allowances quickly happen in single-year compliance, thus increasing abatement costs. The provision of inter-period emission credits banking and borrowing in a multi-period compliance phase can give emitters flexibility in emission compliance, which practices world-widely. In this study, we investigate the impact of carbon trading with inter-temporal emission credits borrowing and banking on a production–inventory–distribution system’s supply chain network decision-making and its compliance strategies by proposing a novel two-stage stochastic programming. A scenario-based robust optimization approach is presented with a post-optimization stage to obtain robustness-profit-environment balanced decision-making considering uncertain demand and stochastic carbon-trading price. The results suggests emitters should adopt specific greener techniques to reduce related emissions with priority under carbon-trading policies. The results also show the provision of carbon credits borrowing and banking has a positive influence on enhancing the efficiency in supply chain economic and ecological performance. Besides, given the flexible provisions, the manager can reallocate emission credits according to its business’s operation, and transfer more emission credits to periods of higher carbon-trading price. This findings also suggest banking in early periods instead of carelessly borrowing from future, for uncertainty in future business might make it harder or impossible to comply with emission regulation at last. To regulators, it should prevent borrowing explicitly or allow it only to a limited extent.

Simulation-Based Approach for Multi-Echelon Inventory System Selection: Case of Distribution Systems

Due to the current complexity of the supply chain, multi-echelon inventory management has become challenging while also being an interesting field of research as it allows efficient control of supply chain interdependencies. It became clear to many researchers that analytical models are no longer effective for addressing the multi-echelon inventory management problem. Simulation can be used to assess and quantify the impact of each inventory strategy on a supply chain performance. Our paper aims to provide a simulation-based approach to guide decision makers select and validate a multi-echelon distribution inventory system. The proposed approach is composed of four major steps that involve characterization of the current supply chain, conceptual modeling of the multi-echelon inventory system alternatives, and finally, simulation modeling using appropriate simulation software to compare and test different options. The approach was also tested and validated through an application to the case of the Moroccan pharmaceutical products supply chain in the public sector. The results of the simulation demonstrated that adopting an installation stock policy at all levels of the supply chain with an allocation of safety stocks in the most downstream stages is the best and most appropriate alternative for the pharmaceutical supply chain under study.

Evaluation and control of inventory distribution systems with quantity based shipment consolidation

AbstractJoint consideration of inventory and shipment decisions is an important aspect of obtaining economically and environmentally sustainable distribution systems. We consider this issue in the context of a one‐warehouse‐multiple‐retailer inventory system with quantity‐based shipment consolidation to groups of nonidentical retailers facing Poisson demand. The system is centralized, with free information sharing and access to real‐time point of sale data. Thus, demand information at the retailers is immediately conveyed upstream to the warehouse without any fixed ordering costs. However, fixed costs associated with handling and transporting goods from the warehouse to the retailers are reflected in the shipment consolidation policy. Stock replenishments at the warehouse are made from an outside supplier/manufacturer according to an (R, Q) policy. For this system, we derive an exact recursive method for determining the inventory level distributions at the retailers. This allows us to evaluate the expected inventory and shipment costs, fill‐rates, and transport emissions for the entire system. We also show how to optimize the system by providing bounds on the optimal shipment quantities and the warehouse reorder level.

ПРАКТИЧНІ АСПЕКТИ УПРАВЛІННЯ МАТЕРІАЛЬНИМИ ЗАПАСАМИ ТОРГІВЕЛЬНИХ ПІДПРИЄМСТВ

The article considers the methodological bases of the inventory management process and the inventory distribution system of non- food and food retail enterprises of Ukraine. In particular, it was found that the inventory management process of the investigated enterprises is based on such models and methods as the model with a fixed period of time between orders, the principles of the theory of constraints; model of the economic size of the order, method of ABC analysis; a model with a fixed period of time between orders, a method of combined ABC and XYZ analysis. In addition, it was determined that enterprises use centralized and decentralized systems in the process of distributing stocks. As a result of the analysis, a number of advantages and disadvantages of the mentioned processes were highlighted. In particular, the key advantages of the inventory management process of trading enterprises include: taking into account the factor of seasonality and the location of stores; weekly tracking of store sales intensity; the possibility of taking into account the demand of each chain store; use of direct delivery services from suppliers, which allows to take into account perishable categories of goods; use of EDI electronic data exchange, etc. The main shortcomings include: untimely response of managers to possible unexpected circumstances of the external environment, which leads to an excess or shortage of goods in stores; unreasonableness of changes in the stock buffer when making decisions about the amount of material stock; insufficient validity of the calculation of the insurance reserve, lack of a clear distribution of the size of the insurance reserve by groups; the difficulty of promptly and fully resolving issues related to the purchase of goods, etc. Prospects for further research are the development of proposals for solving the identified problems, in particular, recommendations for optimizing the process of inventory management of trading enterprises.

Technical Note–A Simple Heuristic Policy for Stochastic Distribution Inventory Systems with Fixed Shipment Costs

Inventory Management in Stochastic Distribution Systems

Supplement to 'A Simple Heuristic Policy for Stochastic Distribution Inventory Systems with Fixed Shipment Costs'

As a supplement to Zhu et al. (2020), this document consists of five parts. First, it provides technical proofs of some theoretical results in Zhu et al. (2020). Second, it introduces some preliminary results on stochastic distribution systems with fixed shipment costs. Third, it provides some examples and illustrations on the modified echelon (r,Q) policies (and some related concepts) studied in Zhu et al. (2020). Fourth, it presents some explicit performance bounds that depends on system primitives for the modified echelon (r,Q) policies in stochastic distribution systems. Finally, extensive numerical experiments are conducted to test the effectiveness of the modified echelon (r,Q) policies. Specifically, the numerical studies show that the modified echelon (r,Q) policies perform well with an average gap of about 5% above the cost lower bound, 2) outperform the echelon-stock (r, Q) policy used in Chen and Zheng (1997), and 3) have robust performances with respect to the allocation rule at the warehouse.

An energy-efficient scheduling and rescheduling method for production and logistics systems†

Scheduling can be defined as the allocation of available resources over time while optimising a set of criteria like early completion time of task, holding inventory, etc. The complexity of the scheduling problem, already known to be high, increases if dynamic events and disruptions are considered. In addition, in production and logistics, designers of scheduling systems must consider sustainability-related expectations. This paper presents an energy-efficient scheduling and rescheduling method (named Green Rescheduling Method, GRM). GRM aims at the solving of the dynamic scheduling problem under the condition of a certain level of routing flexibility enabling the reassignment of tasks to new resources. The key performance indicators integrated into the proposed GRM are effectiveness and efficiency-oriented. Applications concern the domains of production and logistics. In order to assess the proposed approach, experimentations have been made and results illustrate the applicability of GRM to build efficient and effective scheduling and rescheduling both for flexible manufacturing systems and inventory distribution systems in a physical internet network. A mathematical formulation for flexible job shop problem with energy consumption is also proposed using mixed Integer programming to evaluate the performance of the predictive part of GRM.

Controlling distribution inventory systems with shipment consolidation and compound Poisson demand

We consider a one-warehouse-multiple-retailer inventory system where the retailers face stochastic customer demand, modelled as compound Poisson processes. Deliveries from the central warehouse to groups of retailers are consolidated using a time based shipment consolidation policy. This means that replenishment orders have to wait until a vehicle departures, which increases the lead time for the retailers and therefore also the safety stock. Thus, a trade-off exists between expected shipment costs and holding costs. Our aim is to determine the shipment intervals and the required amount of safety stock for each retailer and the warehouse to minimize total cost, both for backorder costs and fill rate constraints. Previous work has focused on exact solutions which are computationally demanding and not applicable for larger real world problems. The focus of our present work is on the development of computationally attractive heuristics that can be applied in practice. A numerical study shows that the proposed heuristics perform well compared to the exact cost minimizing solutions. We also illustrate that the approaches are appropriate for solving real world problems using data from a large European company.

Perancangan Purwarupa Sistem Informasi Online Pendistribusian dan Persediaan Logistik Saat Tanggap Darurat Bencana di BPBD Pidie Jaya

<p>Logistics supply when emergency of disaster comes up that have some problems to be considered much as setting up of emergency operations center irregularly, less coordination between sectors, the data of victims is not properly recorded, and the logistics supply not appropriate with the need of victims. These problems occured because there are no information connected between sectors related to victim data, and the aid that has been fulfilled is very urgent logistics at the disaster site. Information system for distribution and logistics supplies during disaster response is needed to realize effective and efficient distribution. This information system design includes planning, system analysis, collecting data, system design, system testing and implementation. This research was conducted at BPPD office in Pidie Jaya Regency. This information distribution and logistics inventory system that is designed will simplify and accelerate the process of recording in distribution and logistics supply. The results of this system can be introduced to society, so that when disaster occurs the community will receive information quickly and accurately related to distribution and logistics supply</p>

Multi-echelon Supply Chain Model for Deteriorating Products in a Fuzzy Deterioration Environment

Purpose: This research analyses the optimal inventory strategy for a deteriorating product with imprecise deterioration rate in a single supplier-buyer supply chain system with realistic factors. Design/methodology/approach: The integration of production and distribution inventory system is crucial in practice for minimizing a firm's cost while the effect of deterioration cannot be ignored as it affects the entire inventory system. Nowadays managers have begun to recognize that effectively managing deterioration risks in their business operations plays an important role in successfully managing their inventories. Here, the deterioration rate is treated as the triangular fuzzy number. Also we use the extension principle method to define the membership function of the fuzzy total cost and defuzzify by the centroid to find the estimate of the total cost in the fuzzy sense. Findings: A methodology has been proposed through mathematical model which involves designing an iterative algorithm to achieve optimal decisions such as order lot-size and total number of deliveries from the supplier to buyer. Originality value: The effects of varying the central parameter values on the optimal solution are performed by numerical and sensitivity analysis so as to highlight the differences between crisp and the fuzzy cases.

Optimal randomized ordering policies for a capacitated two-echelon distribution inventory system

Abstract We propose a new formulation for controlling inventory in a two-echelon distribution system consisting of one warehouse and multiple non-identical retailers. In such a system, customer demand occurs based on a normal distribution at the retailers and propagates backward through the system. The warehouse and the retailers have a limited capacity for keeping inventory and if they are not able to fulfill the demand immediately, the demand will be lost. All the locations review their inventory periodically and replenish their inventory spontaneously based on a periodic Randomized Ordering (RO) policy. The RO policy determines order quantity of each location in each period by subtracting corresponding on-hand inventory at the beginning of that period from a deterministic decision variable. We propose a mathematical model to find the optimal RO policies such that an average systemwide cost consisting of ordering, holding, shortage, and surplus costs is minimized. We use the first and second moments of on-hand inventory as auxiliary variables. A remarkable advantage of this model is calculating the immediate fill rate of all locations without adding new variables and facing the curse of dimensionality. Using two numerical examples with stationary and non-stationary demand settings, we validate and evaluate the proposed model. For validation, we simulate the optimal RO policy and demonstrate that the optimal first and second moments of on-hand inventory from our model reasonably follow the corresponding moments obtained through simulation. Furthermore, we evaluate the RO policy by drawing a comparison between the optimal RO policy and the optimal well-known R , s n ∗ , S n ∗ policy. The results confirm that the RO policy could outperform ( R , s , S ) policy in terms of the average systemwide annual cost.

Approximate evaluation of continuous review (R,Q) policies in two-echelon inventory systems with stochastic transportation

This paper considers a distribution inventory system that consists of a single warehouse and several retailers. Customer demand arrives at the retailers according to a continuous-time renewal process. Material flow between echelons is driven by reorder point/order quantity inventory control policies. Our objective in this setting is to calculate the long-run inventory, backorder and customer service levels. The challenge in this system is to characterize the demand arrival process at the warehouse. We present a Markovian methodology to elucidate and approximate this process. We illustrate the use of this methodology in the distribution inventory system under stochastic transportation times with identical and non-identical retailers.

고정IP 기반의 IPv6를 이용한 사물인터넷 제품 추적 및 재고관리 시스템 제언

IPv4 주소가 고갈됨에 따라 한계점을 해결하기 위해 나타난 IPv6 주소체계가 서서히 다양한 분야에서 활용되고 있다. 최근에는 다양한 사물과 네트워킹 할 수 있는 사물인터넷(IoT) 제품들이 등장하기 시작하였다. 사물인터넷이 많은 분야에 점차 적용되고 네트워킹 기술이 포함된 전자기기 보급이 증가함에 따라, 각 기기마다 IPv6의 IP주소를 부여받게 될 것이다. 사물조차도 주소를 가지게 되면서 IP주소 관리시스템이 더욱 중요하다. IP주소를 가지고 있는 전자기기가 더 이상 사용되지 않고 있을 때, 그 전자기기의 IP주소를 추적 및 회수하기 위한 보완된 물류관리시스템이 필요하다. 본 논문에서는, 사물인터넷 제품에 각각 고정된 IPv6의 IP주소를 할당하여 이러한 IP주소와 네트워크를 기반으로 한 위치기반서비스를 이용하여 각 제품의 현재 위치를 추적하고, 창고 내의 제품을 관리하고자 한다. 필요시 IP 주소를 회수할 수 있는 새로운 물류추적 및 재고관리 시스템을 제언한다. The IPv6 which solved the exhaustion problem of IPv4's IP address is going to be used for many kinds of industries. As a result, there are some products which can be connected to other connectable things, it called Internet of Things (IoT). With growing new propagated products including networking, each product can get an IP address of IPv6, which means it is possible that things also have their own IP addresses. Thus, IP address management system is more important and needs tracking and collecting system for unused products with IP addresses. This study suggests new distribution tracking and inventory management system for IoT products, which offers a current location of things and manages stocks in the warehouse with the static IP address and the location-based service.

Simulation-based optimization framework for multi-echelon inventory systems under uncertainty

Inventory optimization is critical in supply chain management. The complexity of real-world multi-echelon inventory systems under uncertainties results in a challenging optimization problem, too complicated to solve by conventional mathematical programing methods. We propose a novel simulation-based optimization framework for optimizing distribution inventory systems where each facility is operated with the (r, Q) inventory policy. The objective is to minimize the inventory cost while maintaining acceptable service levels quantified by the fill rates. The inventory system is modeled and simulated by an agent-based system, which returns the performance functions. The expectations of these functions are then estimated by the Monte-Carlo method. Then the optimization problem is solved by a cutting plane algorithm. As the black-box functions returned by the Monte-Carlo method contain noises, statistical hypothesis tests are conducted in the iteration. A local optimal solution is obtained if it passes the test on the optimality conditions. The framework is demonstrated by two case studies.

Simulating Demand Uncertainty and Inventory Control Variability of Multi-Echelon Distribution Supply Chain

Development of simulation models allows performance analysis of multi-echelon inventory networks, and this part of supply chain is not well-established research area. Moreover, by encapsulating all major characteristics of multi-echelon system, the simulation modeling does not allow only its study, but also it provides the means to achieve the desired system performance. This paper deals with a multi-echelon distribution inventory system made of suppliers, distributors and retailers. The retailer faces stochastic demands placed by customers and replenishing from its distributor, which in turn procures from its supplier at the upstream of the chain. The main purpose of this simulation model is to analyze the multi-echelon distribution system behavior according some key performance metrics such as cost and backorder, as well as customer service level at each echelon.

Coordination mechanism for a deteriorating item in a two-level supply chain system

The subject of the coordination between the suppliers and the buyers in multi-echelon inventory-distribution systems has been studied by many researchers. This paper considers a supply chain including a manufacturer and several buyers and assumes that the inventory items deteriorate over time and its inventory level decreases. In order to determine the order policies, coordination over the supply chain is achieved by scheduling the buyers’ delivery days and their coordination with the manufacturer’s production cycle. A mathematical model is developed and analyzed. To test the efficiency of the proposed model, two other models with the supposition of lot-sizing policies with common order cycle and independent deciding are also developed. In comparison to the other two models, the numerical results show that the synchronizing model of production and delivery cycles works better and has less total cost. In addition, in order to encourage the buyers in cooperation, a model on profit sharing is proposed that equitably shares the total savings with all the parties.

Demand selection decisions for a multi-echelon inventory distribution system

In this paper, we study an integrated demand selection and multi-echelon inventory control problem that generalizes the classical deterministic single distribution centre (DC) multi-retailer model by incorporating demand selection decisions. In addition to the ordering and holding cost components, a concave operating cost of the DC and a capacity on the total market demand served are also considered. For given revenue and cost parameters, the problem is to determine which sets of demand to fulfill and which multi-echelon inventory control policy to implement so as to maximize the net profit. We show that the problem can be formulated as a nonlinear discrete optimization model. We analyse the structural properties of the model and, based on these, outline an approach to solve the model efficiently. We also present some interesting managerial insights obtained from the numerical experiments.

A model for heuristic coordination of real life distribution inventory systems with lumpy demand

This paper presents an approximation model for optimizing reorder points in one-warehouse N-retailer inventory systems subject to highly variable lumpy demand. The motivation for this work stems from close cooperation with a supply chain management software company, Syncron International, and one of their customers, a global spare parts provider. The model heuristically coordinates the inventory system using a near optimal induced backorder cost at the central warehouse. This induced backorder cost captures the impact that a reorder point decision at the warehouse has on the retailers’ costs, and decomposes the multi-echelon problem into solving N+1 single-echelon problems. The decomposition framework renders a flexible model that is computationally and conceptually simple enough to be implemented in practice.A numerical study, including real data from the case company, shows that the new model performs very well in comparison to existing methods in the literature, and offers significant improvements to the case company. With regards to the latter, the new model in general obtains realized service levels much closer to target while reducing total inventory.

A Semi-Markov decision problem for proactive and reactive transshipments between multiple warehouses

Lateral transshipments are an effective strategy to pool inventories. We present a Semi-Markov decision problem formulation for proactive and reactive transshipments in a multi-location continuous review distribution inventory system with Poisson demand and one-for-one replenishment policy. For a two-location model we state the monotonicity of an optimal policy. In a numerical study, we compare the benefits of proactive and different reactive transshipment rules. The benefits of proactive transshipments are the largest for networks with intermediate opportunities of demand pooling and the difference between alternative reactive transshipment rules is negligible.

A distribution inventory model with transshipments from a support warehouse

This article considers a distribution inventory system consisting of N retailers and a regional support warehouse, all being replenished from a central warehouse/outside supplier. For the case where stock-outs occur, the retailers receive transshipments from the support warehouse at an extra cost. A model is presented for cost evaluation and optimization of the reorder points in the system under fill rate constraints. The solution method is designed to handle large real-life systems and is fast enough to be directly implemented in practice. A numerical study illustrates that (i) the model renders near-optimal solutions; (ii) the value of using a support warehouse can be significant even for large transshipment costs; and (iii) significant cost savings can be obtained using the proposed model. Using real data for a sample of 50 representative products, the proposed model reduces the expected holding and transshipment costs by 29% while still meeting target fill rates. [Supplemental materials are available for this article. Go to the publisher's online edition of IIE Transactions to view the supplemental file.]