Linear integrated location-inventory models for service parts logistics network design

We present two integrated network design and inventory control problems in service-parts logistics systems. Such models are complicated due to demand uncertainty and highly nonlinear time-based service level constraints. Exploiting unique properties of the nonlinear constraints, we provide an equivalent linear formulation under part-warehouse service requirements, and an approximate linear formulation under part service requirements. Computational results indicate the superiority of our approach over existing approaches in the literature

Design and Control of Warehouse Order Picking: a literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.Order picking;Logistics;Warehouse Management

Exact Methods for Multi-echelon Inventory Control : Incorporating Shipment Decisions and Detailed Demand Information

Recent advances in information technologies and an increased environmental awareness have altered the prerequisites for successful logistics. For companies operating on a global market, inventory control of distribution systems is often an essential part of their logistics planning. In this context, the research objective of this thesis is: To develop exact methods for stochastic inventory control of multi-echelon distribution systems incorporating shipment decisions and/or detailed demand information.The thesis consists of five scientific papers (Paper I, II, III, IV and V) preceded by a summarizing introduction. All papers study systems with a central warehouse supplying a number of non-identical local warehouses (retailers) facing stochastic demand. For given replenishment policies, the papers provide exact expressions for evaluating the expected long-run system behavior (e.g., distributions of backorders, inventory levels, shipment sizes and expected costs) and present optimization procedures for the control variables. Paper I and II consider systems where shipments from the central warehouse are consolidated to groups of retailers and dispatched periodically. By doing so, economies of scale for the transports can be reached, reducing both transportation costs and emissions. Paper I assumes Poisson customer demand and considers volume-dependent transportation costs and emissions. The model involves the possibility to reserve intermodal (train) capacity in combination with truck transports available on demand. For this system, the expected inventory costs, the expected transportation costs and the expected transport emissions are determined. Joint optimization procedures for the shipment intervals, the capacity reservation quantities, the reorder points and order-up-to levels in the system are provided, with or without emission considerations. Paper II analyses the expected costs of the same system for compound Poisson demand (where customer demand sizes may vary), but with only one transportation mode and fixed transportation costs per shipment. It also shows how to handle fill rate constraints. Paper III studies a system where all stock points use installation stock (R,Q) ordering policies (batch ordering). This implies that situations can occur when only part of a requested retailer order is available at the central warehouse. In these situations, the models in existing literature predominantly assume that available units are shipped immediately (partial delivery). An alternative is to wait until the entire order is available before dispatching (complete delivery). The paper introduces a cost for splitting the order and evaluates a system where optimal choices between partial and complete deliveries are made for all orders. In a numerical study it is shown that significant savings can be made by using this policy compared to systems which exclusively use either partial or complete deliveries. Paper IV shows how companies can benefit from detailed information about their customer demand. In a continuous review base stock system, the customer demand is modeled with independent compound renewal processes at the retailers. This means that the customer inter-arrival times may follow any continuous distribution and the demand sizes may follow any discrete distribution. A numerical study shows that this model can achieve substantial savings compared to models using the common assumption of exponential customer inter-arrival times. Paper V is a short technical note that extends the scope of analysis for several existing stochastic multi-echelon inventory models. These models analyze the expected costs without first determining the inventory level distribution. By showing how these distributions can be obtained from the expected cost functions, this note facilitates the analysis of several service measures, including the ready rate and the fill rate

An inventory control project in a major Danish company using compound renewal demand models

We describe the development of a framework to compute the optimal inventory policy for a large spare-parts’ distribution centre operation in the RA division of the Danfoss Group in Denmark. The RA division distributes spare parts worldwide for cooling and A/C systems. The warehouse logistics operation is highly automated. However, the procedures for estimating demands and the policies for the inventory control system that were in use at the beginning of the project did not fully match the sophisticated technological standard of the physical system. During the initial phase of the project development we focused on the fitting of suitable demand distributions for spare parts and on the estimation of demand parameters. Demand distributions were chosen from a class of compound renewal distributions. In the next phase, we designed models and algorithmic procedures for determining suitable inventory control variables based on the fitted demand distributions and a service level requirement stated in terms of an order fill rate. Finally, we validated the results of our models against the procedures that had been in use in the company. It was concluded that the new procedures were considerably more consistent with the actual demand processes and with the stated objectives for the distribution centre. We also initiated the implementation and integration of the new procedures into the company’s inventory management systemBase-stock policy; compound distribution; fill rate; inventory control; logistics; stochastic processes

Optimal Supply Network with Vendor Managed Inventory in a Healthcare System with RFID Investment Consideration

Supply Chain Management in the healthcare sector faces several significant challenges, including complexity in healthcare systems, high supply chain costs, balancing quality and costs, delay in delivery, product availability from vendors, inventory waste, and unpredictability and uncertainty. Among those challenges, having an effective inventory management system with an optimal supply network is important to improve the match between supply and demand, which would improve the performance of for healthcare firms. Vendor Managed Inventory (VMI) system is a replenishment solution in which the vendor monitors and decides the time and the quantity of the inventory replenishment of their customers subject to their demand information exchange. A VMI contract in the location-inventory assignment problem is a decision tool for management in the healthcare industry, in which it enables the management to have a cost and service effective decision tool to critically re-evaluate and examine all areas of operations in a SC network looking for avenues of optimization. This dissertation is based on a real-world problem arising from one of the world\u27s leading medical implant supply company applied to a chain of hospitals in the province of Ontario. The chain of hospitals under study consists of 147 hospitals located in Ontario, Canada. The vendor is a supplier of three types of medical implants (a heart valve, an artificial knee, and a hip). In Chapter 2 of this dissertation, we present an optimal supply healthcare network with VMI and with RFID consideration, in which we shed light on the role of the VMI contract in the location-inventory assignment problem and integrate it with both the replenishment policy assignment and the Radio Frequency Identification (RFID) investment allocation assignment in healthcare SC networks using both VMI and direct delivery policies. A numerical solution approach is developed in the case of the deterministic demand environment, and we end up with computational results and sensitivity analysis for a real-world problem to highlight the usefulness and validate the proposed model. We extend our research of integrating the VMI contract in the location-inventory assignment problem with the replenishment policy assignment under a deterministic demand environment to include the stochastic demand environment. The impact of the uncertainty of the demand as a random variable following two types of distributions, normal and uniform distributions, is studied in Chapter 3. Motivated by the lack of investigations and comparative studies dealing with the preference of dealing with VMI contracts to other traditional Retailer Managed Inventory (RMI) systems, we provide in Chapter 4 of this dissertation a comparative study in which we compare the total cost of the VMI system with another two situations of traditional RMI systems: first, a traditional RMI system with a continuous replenishment policy for all hospitals and with assigned storage facilities and second, a traditional RMI system with a direct delivery policy for all hospitals without assigning a storage facility. Computational results, managerial insights, sensitivity analysis, and solution methodologies are provided in this dissertation. Keywords: Vendor Managed Inventory, healthcare system, location-inventory, RFID technology, supply-chain network, stochastic demand, location-inventory assignment problem, and retailer managed Inventory

A Single-Product Inventory Model for Multiple Demand Classes

We consider a single-product inventory system that serves multiple demand classes, which differ in their shortage costs or service level requirements. We assume a critical-level control policy, and show the equivalence between this inventory system and a serial inventory system. Based on this equivalence, we develop a model for cost evaluation and optimization, under the assumptions of Poisson demand, deterministic replenishment lead-time, and a continuous-review (Q, R) policy with rationing. We propose a computationally-efficient heuristic and develop a bound on its performance. We provide a numerical experiment to show the effectiveness of the heuristic and the value from a rationing policy. Finally, we describe how to extend the model to permit service times, and to embed within a multi-echelon setting

Theory and Practice of Supply Chain Synchronization

In this dissertation, we develop strategies to synchronize component procurement in assemble-to-order (ATO) production and overhaul operations. We focus on the high-tech and mass customization industries which are not only considered to be very important to create or keep U.S. manufacturing jobs, but also suffer most from component inventory burden. In the second chapter, we address the deterministic joint replenishment inventory problem with batch size constraints (JRPB). We characterize system regeneration points, derive a closed-form expression of the average product inventory, and formulate the problem of finding the optimal joint reorder interval to minimize inventory and ordering costs per unit of time. Thereafter, we discuss exact solution approaches and the case of variable reorder intervals. Computational examples demonstrate the power of our methodology. In the third chapter, we incorporate stochastic demand to the JRPB. We propose a joint part replenishment policy that balances inventory and ordering costs while providing a desired service level. A case study and guided computational experiments show the magnitudes of savings that are possible using our methodology. In the fourth chapter, we show how lack of synchronization in assembly systems with long and highly variable component supply lead times can rapidly deteriorate system performance. We develop a full synchronization strategy through time buffering of component orders, which not only guarantees meeting planned production dates but also drastically reduces inventory holding costs. A case study has been carried out to prove the practical relevance, assess potential risks, and evaluate phased implementation policies. The fifth chapter explores the use of condition information from a large number of distributed working units in the field to improve the management of the inventory of spare parts required to maintain those units. Synchronization is again paramount here since spare part inventory needs to adapt to the condition of the engine fleet. All needed parts must be available to complete the overhaul of a unit. We develop a complex simulation environment to assess the performance of different inventory policies and the value of health monitoring. The sixth chapter concludes this dissertation and outlines future research plans as well as opportunities

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications