Inventory Location Research Articles

A network design model considering inventory cost from a third party logistics perspective

The importance of third party logistics (3PLs) service providers is increasing in supply chain management, particularly in warehousing and transportation services as clients expect 3PLs to improve lead times, fill rates, and inventory levels. Therefore, in a dynamic and uncertain business environment, 3PLs are under pressure to meet client service requirements. Few studies have addressed the problem of logistic network design from viewpoint of 3PLs. The main objective of this paper is to propose a new network design problem from 3PLs perspectives by considering inventory to determine economic order quantity. This paper proposes a new nonlinear mixed integer programming model for integrated logistics network design that in facility location-allocation and inventory location problems. To optimize the model, new auxiliary variables and constraints are added. The model was solved by using DICOPT solver.

An integrated inventory location smodel considering all-unit quantity discount

One of the recent areas in distribution network design is integrated inventory location problems, which jointly determines the inventory control decisions and facility location decisions of a distribution network. A typical distribution network consists of suppliers, several retailers, and several distribution centers. Distribution centers order products from suppliers to fulfil demands of retailers. To achieve risk pooling benefits, inventory of several retailers is aggregated into one distribution center. This situation has made distribution centers more likely to take the advantage of quantity discount from suppliers. However, most previous models have investigated the problem under the basic economic order quantity EOQ with (Q, r) inventory policy and yet quantity discount has not been considered. This paper shows that considering quantity discount instead of EOQ policy can reduce the total cost and change the optimal configuration of the networks.

Minimizing transportation cost of a joint inventory location model using modified adaptive differential evolution algorithm

Transportation is a key issue in supply chain management and is a major concern for a company. This paper considers a joint-location inventory problem involving a set of suppliers producing different products and a set of retailers where some retailers are treated as distribution centers (DCs). The problem is to determine which retailers to be assigned as DCs, which retailers to receive direct shipments, how much of the retailer’s demand to allocate to the DCs, and how much of the DC’s demand is to be met by different suppliers. The problem is formulated as a mixed integer model and it has been solved through an adaptive differential evolution algorithm known as modified J. Adaptive Differential Evolution. The solutions obtained are compared with that of simple genetic algorithm. This paper also shows that the proposed model is robust in nature and offers near-optimal results for different distributions. The sum of the cost of establishing some retailers as DCs and the total transportation cost incurred in shipping products from the suppliers to the retailers via DCs(for some retailers) or directly (for the other retailers) is also compared with the total transportation cost incurred when all the products are shipped directly from the suppliers to the retailers.

Maintaining the confidentiality of plot locations by exploiting the low sensitivity of forest structure models to different spectral extraction kernels

The United States Forest Service Forest Inventory and Analysis (FIA) unit maintains a large national network of inventory plots. While the consistency and extent of this network make FIA data attractive for ecological modelling, the FIA is charged by statute not to publicly reveal inventory plot locations. However, use of FIA plot data by the remote sensing community often requires that plot measurements be matched with spatially correspondent values from spectral or geographic data layers. Extracting spatial data in a known way and associating it with plot information leaves open the possibility that a user might use extracted spatial characteristics and a moving window filter to directly infer the plot's location. Direct inference of plot location in this way would be impossible, however, if the original method of sampling the geographic data was unknown. Tests using five Landsat scenes covering a wide range of ecological types showed that varying the weights of pixels within approximately 50 m of the plot centre has little effect on the quality of subsequent models predicting basal area. This finding may support the development of automated extraction routines that vary (perhaps randomly) the geographic data extraction process and therefore increase the security of FIA plot locations.

Using Extant Data to Determine Management Direction in Family Forests

This study investigated the differences between multiple-objective-, timber-, and non-timber-motivated family forest landowner groups in the southeastern states of Alabama, Georgia, and South Carolina. Our focus was primarily to develop a classification scheme using easily available location-specific secondary data associated with family forest owners such that we may be able to identify the likely management direction for particular parcels of forestland in the future. Using nonparametric discriminatory analysis procedures we found that the biophysical, socioeconomic, and demographic factors best differentiated the landowner groups. With all the variables used to develop the classification scheme in this study known, a priori—that is, before the landowner on a Forest Inventory and Analysis (FIA) plot location is contacted for the National Woodland Owner Survey (NWOS)—it may be possible to predict the motivational membership type of a future landowner with known woodlot (FIA) and demographic (Census) attributes.

LLE’s High-Pressure DT-Fill Process Control System

The OMEGA laser at the University of Rochester’s Laboratory for Laser Energetics (UR/LLE) implodes fusion targets that contain cryogenic solid deuterium-tritium (DT) ice layers. These ICF targets are fabricated in a high-pressure DT-fill process. This paper describes the integration and control of this DT-fill process.The appropriate safety-control response during the DT-fill process depends on the location of the tritium inventory and where the containment alarm is detected. A control response that is deemed appropriate earlier in the fill process could be a dangerous action at a later point in the fill process. The control system must adapt as the DT inventory moves through the process train.This is achieved by defining eight “fill states” in the fill process. The control system transitions to the appropriate fill state as the DT fill progresses. The fill state reflects the tritium location, pressure, and temperature. Steps are taken to ensure that the tritium location and the fill state are in agreement. The control system monitors the containment system’s integrity and will take the appropriate action, based on the tritium location and the type of containment failure. This approach not only ensures process safety, but also maximizes the productivity by executing process pauses (in lieu of aborts) when conditions allow.

A Distribution Network Design model for deteriorating item

In this paper, we study the Distribution Network Design problem integrating production, inventory and facilities location, involving a single supplier, some potential Distribution Centres (DCs) and multiple retailers. Distinct from traditional inventory location problems, the product in consideration is deteriorating item of which the deterioration, production and demand rates are all constant. Thus, the problem is to determine how many DCs to be set up, where to locate them, how to serve the retailers using these DCs, as well as the optimal production and inventory policies for the whole distribution network. The goal is to minimise the total deterioration, production, inventory, transportation and facilities location cost. We formulate this problem as a set partitioning mix-integer programming model. This model is a non-deterministic polynomial time-hard problem, so a meta-heuristic solution approach is introduced based on Genetic Algorithms (GA). Numerical examples are given to illustrate the application of the algorithm, and show that GA is an efficient solution approach for this problem.

Demand Allocation in Systems with Multiple Inventory Locations and Multiple Demand Sources

We consider the problem of allocating demand that originates from multiple sources among multiple inventory locations. Demand from each source arrives dynamically according to an independent Poisson process. The cost of fulfilling each order depends on both the source of the order and its fulfillment location. Inventory at all locations is replenished from a shared production facility with a finite production capacity and stochastic production times. Consequently, supply lead times are load dependent and affected by congestion at the production facility. Our objective is to determine an optimal demand allocation and optimal inventory levels at each location so that the sum of transportation, inventory, and backorder costs is minimized. We formulate the problem as a nonlinear optimization problem and characterize the structure of the optimal allocation policy. We show that the optimal demand allocations are always discrete, with demand from each source always fulfilled entirely from a single inventory location. We use this discreteness property to reformulate the problems as a mixed-integer linear program and provide an exact solution procedure. We show that this discreteness property extends to systems with other forms of supply processes. However, we also show that supply systems exist for which the property does not hold. Using numerical results, we examine the impact of different parameters and provide some managerial insights.

Improved two‐grade delayed particle swarm optimisation (TGDPSO) for inventory facility location for perishable food distribution centres in Beijing

Resolving inventory and location problems is the most important and fundamental tactical decision in the initial stages of developing a distribution network design. This is especially true for a logistics system dealing with perishable food. To minimise both the total inventory transportation cost of fresh agri‐products and also waste in the supply chain, the evolution of the food supply chain structure is analysed and an inventory location allocation model is presented describing the real‐life problem. The key issues are to describe food demand distribution and to determine the balance of transportation and inventory cost. To improve the quality of the solution, a local search is embedded in the two‐grade delayed particle swarm optimisation. Experimental results demonstrate the algorithm can effectively resolve conflict between different costs and improve development decisions regarding Beijing's perishable food distribution centres.

Adding uncertainty to forest inventory plot locations: effects on analyses using geospatial data

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service alters plot locations before releasing data to the public to ensure landowner confidentiality and sample integrity, but using data with altered plot locations in conjunction with other spatially explicit data layers produces analytical results with unknown amounts of error. We calculated the potential error from using altered location data in combination with other data layers that varied in mean map unit size. The incidence of errors associated with the use of altered plot locations exhibited a strong inverse relationship to the mean map unit size of the other data sets used in the analyses. For a 30 m × 30 m resolution land cover map, plot misclassification rates ranged from 32% to 66%, whereas only 1%–10% of plots were misclassified for ecological subsection data (mean polygon size 9067 km2). Housing density data derived from the US Decennial Census (mean polygon size = 5.7 km2) represented an intermediate condition, with 5%–70% of data points misclassified when altered plot locations were used. These analyses demonstrate the impacts of altering FIA plot locations and represent an important step toward making the FIA database more helpful to a broad variety of end users.

Integrated supply chain design using multi-criteria optimization

Supply chain management (SCM) presents significant opportunities for improving profit margins and reducing cost. It encompasses functional and geographical integration as well as integration of tactical and operational decisions. The functional integration aspects involve purchasing, manufacturing, and logistics within the company and across the supply chain. A supply chain design framework has been developed including linear/mixed integer multi-criteria optimization models for determining the identified supply chain design parameters. The selection of suppliers, determination of production quantities, inventory locations and sizes, selection of transportation method and transported quantities in a multi-stage, multi-level supply chain are investigated. Additional criteria including first-time quality (FTQ) and suppliers on-time delivery risk with and without allowing splitting of customer demand between suppliers are considered. An example of typical automotive power train supply chain design and decision issues is used to illustrate the effect of various factors.

A Heuristic Approach to the Multi-Period Single-Sourcing Problem with Production and Inventory Capacities and Perishability Constraints

The multi-period single-sourcing problem that we address in this paper can be used as a tool for evaluating logistics network designs in a dynamic environment. We consider the assignment of retailers to facilities, taking into account the timing, location, and size of production and inventories, in the presence of various types of constraints. We formulate the problem as a nonlinear assignment problem, and develop efficient algorithms for solving the capacitated lot-sizing subproblems that form the objective function of this formulation. We propose a greedy heuristic, and prove that this heuristic is asymptotically optimal in a probabilistic sense when retailer demands share a common seasonality pattern. In addition, we develop an efficient implementation of the very-large-scale-neighborhood-search method that can be used to improve the greedy solution. We perform extensive tests on a set of randomly generated problem instances, and conclude that our approach produces very high quality solutions in limited time.

Radioactive Waste Incineration-Ash Pellets Sintered with Borosilicate Glass

In Japan, low-level radioactive wastes discarded by research institutions and hospitals are packed into containers and stored. Volume reduction by incineration and compression processing are sometimes attempted; alternatively, the wastes are left in an unprocessed state because neither landfill sites nor disposal methods have been established. Especially, low-level radioactive waste incineration ash presents great problems of security, safety, and stability in inventory location. A safe and appropriate disposal processing method is desired because the bulk density of ash is low; the ash is also easily dispersed. Volume reduction and stabilization for low-level radioactive waste incineration ash were verified for low-temperature sintering method using glass bottle cullet. The proposed method was useful for easy treatment of low-level radioactive waste incineration ash. This report describes the difference between soda lime glass (cullet) and borosilicate glass for the RI ash sintering, and characteristics of RI volatilization and elution from the sintered radioactive waste pellets. The borosilicate glass is used for glass melt solidification of high-level radioactive waste.

Optimizing delivery lead time/inventory placement in a two-stage production/distribution system

In this paper we study a system composed of a supplier and buyer(s). We assume that the buyer faces random demand with a known distribution function. The supplier faces a known production lead time. The main objective of this study is to determine the optimal delivery lead time and the resulting location of the system inventory. In a system with a single-supplier and a single-buyer it is shown that system inventory should not be split between a buyer and supplier. Based on system parameters of shortage and holding costs, production lead times, and standard deviations of demand distributions, conditions indicating when the supplier or buyer(s) should keep the system inventory are derived. The impact of changes to these parameters on the location of system inventory is examined. For the case with multiple buyers, it is found that the supplier holds inventory for the buyers with the smallest standard deviations, while the buyers with the largest standard deviations hold their own inventory.

Valid inequalities for Lagrangian relaxation in an inventory location problem with stochastic capacity

We developed an efficient heuristic to solve a joint location–distribution–inventory model for a three layered supply chain. A firm must locate distribution centers to supply a commodity to spatially distributed retailers with stochastic demand. The solution approach is based on Lagrangian relaxation, improved with validity constraints derived from the finite set of all possible combinations of mean demand and variance. The optimal solution’s lower bound is found through the optimal solution of the dual problem. The dual gap gives a threshold to the heuristic’s error. The heuristic was applied to 98 instances with an average error threshold of 3%.

True versus perturbed forest inventory plot locations for modeling: a simulation study

USDA Forest Service Forest Inventory and Analysis plot information is widely used for timber inventories, forest health assessments, and environmental risk analyses. With few exceptions, true plot locations are not revealed; the plot coordinates are manipulated to obscure the location of field plots and thereby preserve plot integrity. The influence of perturbed plot locations on the development and accuracy of statistical models is unknown. We tested the hypothesis that the influence is related to the spatial structure of the data used in the models. For ordinary kriging we examined the difference in mean square error based on true and perturbed plot locations across a range of spatial autocorrelations. We also examined the difference in mean square error for regression models developed with true and perturbed plot locations across a range of spatial autocorrelations and spatial resolutions. Perturbing plot locations did not significantly influence the accuracy of kriging estimates, but in some situations linear regression model development and accuracy were significantly influenced. Unless the independent variable has high spatial autocorrelation, only coarse spatial resolution data should be used to develop linear regression models.

The multiple disposal facilities and multiple inventory locations rollon–rolloff vehicle routing problem

In the Multiple disposal facilities and multiple inventory locations rollon–rolloff vehicle routing problem (M-RRVRP), one of the very important pickup and disposal problems in the sanitation industry, tractors move large trailers, one at a time, between customer locations such as construction sites and shopping centers, disposal facilities and inventory locations. In this paper, we model the M-RRVRP as a time constrained vehicle routing problem on a multigraph (TVRP-MG). We then formulate the TVRP-MG as a set partitioning problem with an additional constraint and describe an exact method for solving the TVRP-MG. This exact method is based on a bounding procedure that combines three lower bounds derived from different relaxations of the formulation of the problem. Further, we obtain a valid upper bound and show how this bounding procedure can transform the solution of a Lagrangean lower bound into a feasible solution. Our computational results show that the proposed method is very effective in deriving an optimal or near optimal solution to the M-RRVRP in a reasonable amount of computing time. Since the capacitated vehicle routing problem (CVRP) can be transformed into a TVRP-MG, we tested our procedure on 11 instances of the CVRP. Our computational results show that our procedure very effectively found the optimal solution to 7 of the 11 instances of the CVRP. In many cases, our procedure was at least 10 times faster than the procedure proposed by Fukasawa et al. Integer programming and combinatorial optimization, vol. 10. Lecture notes in computer science, vol. 3064. Berlin: Springer; 2004. p. 1–15. Both our procedure and the procedure of Fukasawa et al. Integer programming and combinatorial optimization, vol. 10. Lecture notes in computer science, vol. 3064. Berlin: Springer; 2004. p. 1–15 solved problem E-n76-k10, the most famous CVRP instance that until recently was unsolved.

廃棄物焼却灰の減容化・安定化方法の開発

The low-level radioactive waste generated from research institutions and hospitals etc. is packed into a container and is kept. The volume reduction state by incineration and the compression processing or the unprocessed state because neither landfill sites nor disposal methods have been fixed. Especially, because the bulk density is low, and it is easy to disperse, the low-level radioactive waste incineration ash incinerated for the volume reduction has a big issue problem in security, safety, stability in the inventory location. A safe and appropriate disposal processing method is desired. When the low temperature sintering method in the use of the glass bottle cullet was examined, it was verified that volume reduction and stabilization of low-level radioactive waste incineration ash. The proposed method is useful for the easy treatment of the low-level radioactive waste incineration ash.

Ethics in an operations management course

Graduates of the management major at the University of Pittsburgh at Greensburg find employment in a variety of organizations. As future managers with employees from different professions, students expressed an interest in discussing ethics cases in the operations management class. The semester starts with students familiarizing themselves with various professional and corporate codes of ethics. Throughout the semester a number of short ethics' cases in operations' areas such as inventory management, scheduling, facility location, and product design are introduced to illustrate ethical issues that a manager and his/her employees might face. Students prepare individual responses before the in-class discussions. The semester ends with a long group ethics case discussion and formal case presentations. In the end-of-semester survey, students responded very favorably to an ethics component in the operations management class.

A Supply Chain Model with Reverse Information Exchange

We develop a model and analyze reverse information sharing, a growing business practice in supply chain management in which a manufacturer shares information about supply with a retailer. We model the manufacturer as a production queue with finished goods warehouse, the retailer as an inventory location, and other customers as an external demand stream. In our model, the manufacturer allows the retailer access to inventory status at the warehouse. To take advantage of this new information, the retailer changes from a single-level base-stock policy to a two-level, state-dependent base-stock policy. We provide an exact method for computing performance and develop a procedure for evaluating optimal policy. We demonstrate the impact of the new policy on the manufacturer and other customers. Numerical computations lead to insights about the value of information to the retailer, and to guidelines for the manufacturer on sharing information.