Inventory planning for spare parts networks with delivery time requirements

Motivated by real life, we introduce a new inventory model for spare parts where we explicitly take delivery time requirements into account. In this single-echelon, multilocation network, demand of a customer can be satisfied from multiple warehouses, but only if the customer can be reached from a warehouse within a time limit that is specified in the service contract of the customer. A delivery to a customer from a warehouse other than the closest one is referred to as a lateral transshipment. We develop a fast and accurate approximate algorithm to evaluate the performance of the network under given base stock levels and propose a fast and effective heuristic to set base stock levels. Numerical experiments show that planning with lateral transshipments can lead to cost savings up to 47% when compared to planning without lateral transshipments. Furthermore, we show the importance of taking lateral transshipments into account when designing a spare parts network

Inventory models with lateral transshipments : a review

Lateral transshipments within an inventory system are stock movements between locations of the same echelon. These transshipments can be conducted periodically at predetermined points in time to proactively redistribute stock, or they can be used reactively as a method of meeting demand which cannot be satised from stock on hand. The elements of an inventory system considered, e.g. size, cost structures and service level denition, all in uence the best method of transshipping. Models of many dierent systems have been considered. This paper provides a literature review which categorizes the research to date on lateral transshipments, so that these dierences can be understood and gaps within the literature can be identied

Multicommodity network flow problem with substitution

Multicommodity network flow problems are generalizations of single commodity network flow problems, where a number of commodities flow through the network often sharing common resources such as arc capacities. While the single commodity problem can be solved in polynomial time even when the flow quantities are imposed as integer values only, the integer multicommodity version of the problem with arc capacities is NPhard. We introduce a generalization of the multicommodity network flow problem where substitution is possible amongst commodities. We develop mathematical models as the linear integer programming formulations of two-commodity and three-commodity problems with both commodity-specific and overall arc capacities. We prove that constraint matrices are totally unimodular in the mathematical programming formulations for the uncapacitated versions. We investigate the empirical computational difficulty of capacitated versions of the problem formulations through a computational study with randomly generated problems and statistical analysis with hypothesis testing. In particular, we explore the effect of capacities and the problem size on solution time. Our results show that solution time significantly increases for both two-commodity and three-commodity problems when both overall and commodity-specific capacities exist. Solution time significantly increases when problem size is increased. Finally, we generalized the two and three-commodity models for the multicommodity problem

İkame ürün dağıtım ağlarında stok optimizasyonu ve optimal dağıtım politikaları

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Çok ürünlü stok sistemlerinde ürün stoklarının eşgüdümlü olarak yenilenmesi, özellikle ulaştırma maliyetlerinde oluşan ölçek ekonomileri nedeniyle önemli maliyet kazançları sağlar. Bunun yanı sıra bu tür stok sistemlerinde ürün ikamesi yapılabilmesi, stok maliyetlerini önemli derecede düşürür. Tezde, ürünlerin birbirileri ile ikame edilebildiği çok ürünlü stok sistemlerinde ürün kombinasyonu dağıtım ve stokastik stok yenileme problemi incelenmiştir. Ele alınan problemde ürün stokları eşgüdümlü olarak yenilenmekte ve müşteri talebi firma kaynaklı olarak stoklardaki ürünlerin herhangi bir kombinasyonuyla karşılanabilmektedir. Amaç, sonsuz zaman ufkunda birim zaman başına ortalama maliyeti yaklaşık olarak en küçükleyen ürün kombinasyonu dağıtım ve stok yenileme politikasının belirlenmesidir. Tezde, stok yenileme politikası olarak sürekli gözden geçirme esasına dayanan eşgüdümlü (S,c,s) “can order” politikası kullanılmış ve stok kontrol parametrelerinin belirlenmesinde literatürdeki çalışmalardan faydalanılmıştır. Ürün kombinasyonu dağıtım problemi ise yarı Markov karar süreci olarak modellenmiş ve çözüm için Q faktör fonksiyonunun çok katmanlı yapay sinir ağlarıyla tahmin edildiği ödüllü öğrenme algoritmaları kullanılmıştır. Çalışmada, ürün kombinasyonu dağıtım ve stok yenileme problemini sıralı ve yinelemeli olarak çözen bir algoritma geliştirilmiş ve değişik ölçeklerdeki uygulamalı denemelerde, geliştirilen algoritmanın performansı miyopik politikalarla kıyaslanmıştır. Gerçekleştirilen uygulamalı denemelere göre, geliştirilen algoritmayla elde edilen ürün kombinasyonu dağıtım ve stok yenileme politikalarının ortalama maliyetleri, miyopik politikaların ortalama maliyetlerinden çok daha düşüktür.In multi-product inventory systems, considerably savings in specially transportation costs may be achieved by coordination of replenishment orders for groups of products. Moreover, product substitutions in these systems reduce significantly inventory costs. In this thesis, a fully substitutable multi product system is considered in which customer demands may be satisfied by delivering any combination of products. In the studied system, product substitution is driven by firm and product inventories may be replenished by coordinated control. The aim of the thesis is to determine order fulfillment and replenishment policies minimizing approximately average cost in unit time in infinite horizon. In this thesis, a specific control system is considered which is known as a (S,c,s) type policy, and works in the literature are used to determine the control parameters. The order fulfillment problem is modeled as a semi Markov decision process, and reinforcement learning algorithms with approximation to Q factor function by artificial neural network are used to solve this problem. In the thesis, an algorithm is developed which determines iteratively order fulfillment and (S,c,s) policies for each product in a multi-product inventory system. In numerical examples, it is seen that order fulfillment and replenishment policies determined by the developed algorithm outperform myopic policies

Pooling and polling : creation of pooling in inventory and queueing models

The subject of the present monograph is the ‘Creation of Pooling in Inventory and Queueing Models’. This research consists of the study of sharing a scarce resource (such as inventory, server capacity, or production capacity) between multiple customer classes. This is called pooling, where the goal is to achieve cost or waiting time reductions. For the queueing and inventory models studied, both theoretical, scientific insights, are generated, as well as strategies which are applicable in practice. This monograph consists of two parts: pooling and polling. In both research streams, a scarce resource (inventory or server capacity, respectively production capacity) has to be shared between multiple users. In the first part of the thesis, pooling is applied to multi-location inventory models. It is studied how cost reduction can be achieved by the use of stock transfers between local warehouses, so-called lateral transshipments. In this way, stock is pooled between the warehouses. The setting is motivated by a spare parts inventory network, where critical components of technically advanced machines are kept on stock, to reduce down time durations. We create insights into the question when lateral transshipments lead to cost reductions, by studying several models. Firstly, a system with two stock points is studied, for which we completely characterize the structure of the optimal policy, using dynamic programming. For this, we formulate the model as a Markov decision process. We also derived conditions under which simple, easy to implement, policies are always optimal, such as a hold back policy and a complete pooling policy. Furthermore, we identified the parameter settings under which cost savings can be achieved. Secondly, we characterize the optimal policy structure for a multi-location model where only one stock point issues lateral transshipments, a so-called quick response warehouse. Thirdly, we apply the insights generated to the general multi-location model with lateral transshipments. We propose the use of a hold back policy, and construct a new approximation algorithm for deriving the performance characteristics. It is based on the use of interrupted Poisson processes. The algorithm is shown to be very accurate, and can be used for the optimization of the hold back levels, the parameters of this class of policies. Also, we study related inventory models, where a single stock point servers multiple customers classes. Furthermore, the pooling of server capacity is studied. For a two queue model where the head-of-line processor sharing discipline is applied, we derive the optimal control policy for dividing the servers attention, as well as for accepting customers. Also, a server farm with an infinite number of servers is studied, where servers can be turned off after a service completion in order to save costs. We characterize the optimal policy for this model. In the second part of the thesis polling models are studied, which are queueing systems where multiple queues are served by a single server. An application is the production of multiple types of products on a single machine. In this way, the production capacity is pooled between the product types. For the classical polling model, we derive a closedform approximation for the mean waiting time at each of the queues. The approximation is based on the interpolation of light and heavy traffic results. Also, we study a system with so-called smart customers, where the arrival rate at a queue depends on the position of the server. Finally, we invent two new service disciplines (the gated/exhaustive and the ??-gated discipline) for polling models, designed to yield ’fairness and efficiency’ in the mean waiting times. That is, they result in almost equal mean waiting times at each of the queues, without increasing the weighted sum of the mean waiting times too much

Service Inventory Management : Solution techniques for inventory systems without backorders

Koole, G.M. [Promotor]Vis, I.F.A. [Copromotor