R.H. Teunter (Ruud)
http://repub.eur.nl/ppl/968/
List of Publicationsenhttp://repub.eur.nl/logo.jpg
http://repub.eur.nl/
RePub, Erasmus University RepositoryAn easy derivation of the order level optimality condition for inventory systems with backordering
http://repub.eur.nl/pub/15482/
Tue, 01 Jul 2008 00:00:01 GMT<div>R.H. Teunter</div><div>R. Dekker</div>
We analyze the classical inventory model with backordering, where the inventory position is controlled by an order level, order quantity policy. The cost for a backorder contains a fixed and a time-proportional component. Demand can be driven by any discrete process. Order lead times may be stochastic and orders are allowed to cross. The optimality condition for the order-level, given some predetermined order quantity, is derived using an easy and insightful marginal cost analysis. It is further shown how this condition can easily be (approximately) rewritten in well-known forms for special cases.Simple heuristics for push and pull remanufacturing policies
http://repub.eur.nl/pub/14822/
Fri, 01 Dec 2006 00:00:01 GMT<div>E.A. van der Laan</div><div>R.H. Teunter</div>
Inventory policies for joint remanufacturing and manufacturing have recently received much attention. Most efforts, though, were related to (optimal) policy structures and numerical optimization, rather than closed form expressions for calculating near optimal policy parameters. The focus of this paper is on the latter. We analyze an inventory system with unit product returns and demands where remanufacturing is the cheaper alternative for manufacturing. Manufacturing is also needed, however, since there are less returns than demands. The cost structure consists of setup costs, holding costs, and backorder costs. Manufacturing and remanufacturing orders have non-zero lead times. To control the system we use certain extensions of the familiar (s, Q) policy, called push and pull remanufacturing policies. For all policies we present simple, closed form formulae for approximating the optimal policy parameters under a cost minimization objective. In an extensive numerical study we show that the proposed formulae lead to near-optimal policy parameters.Value of Information in Closed Loop Supply Chains
http://repub.eur.nl/pub/14821/
Sun, 01 Jan 2006 00:00:01 GMT<div>M.E. Ketzenberg</div><div>E.A. van der Laan</div><div>R.H. Teunter</div>
We explore the value of information (VOI) in the context of a firm that faces uncertainty with respect to demand, product return, and product recovery (yield). The operational decision of interest in matching supply with demand is the quantity of new product to order. Our objective is to evaluate the VOI from reducing one or more types of uncertainties, where value is measured by the reduction in total expected holding and shortage costs. We start with a single period model with normally distributed demands and returns, and restrict the analysis to the value of full information (VOFI) on one or more types of uncertainty. We develop estimators that are predictive of the value and sensitivity of (combinations of) different information types. We find that there is no dominance in value amongst the different types of information, and that there is an additional pay-off from investing in more than one type. We then extend our analysis to the multi-period case, where returns in a period are correlated with demands in the previous period, and study the value of partial information (VOPI) as well as full information. We demonstrate that our results from the single period model (adapted for VOPI) carry-over exactly. Furthermore, a comparison with uniformly distributed demand and return show that these results are robust with respect to distributional assumptions.The distribution-free newsboy problem with resalable returns
http://repub.eur.nl/pub/11888/
Sun, 18 Sep 2005 00:00:01 GMT<div>J.A.M. Mostard</div><div>M.B.M. de Koster</div><div>R.H. Teunter</div>
We study the case of a catalogue/internet mail order retailer selling style goods and receiving large numbers of commercial returns. Returned products arriving before the end of the selling season can be resold if there is sufficient demand. A single order is placed before the season starts. Excess inventory at the end of the season is salvaged and all demands not met directly are lost. Since little historical information is available, it is impossible to determine the shape of the distribution of demand. Therefore, we analyze the distribution-free newsboy problem with returns, in which only the mean and variance of demand are assumed to be known. We derive a simple closed-form expression for the distribution-free order quantity, which we compare to the optimal order quantities when gross demand is assumed to be normal, lognormal or uniform. We find that the distribution-free order rule performs well when the coefficient of variation (CV) is at most 0.5, but is far from optimal when the CV is large.Dynamic lot sizing with product returns
http://repub.eur.nl/pub/6557/
Mon, 18 Apr 2005 00:00:01 GMT<div>R.H. Teunter</div><div>Z.P. Bayindir</div><div>W. van den Heuvel</div>
We address the dynamic lot sizing problem for systems with product returns. The demand
and return amounts are deterministic over the finite planning horizon. Demands can be
satisfied by manufactured/procured new items, but also by remanufactured returned items.
The objective is to determine those lot sizes for manufacturing and remanufacturing that
minimize the total cost composed of holding cost for returns and serviceable products and
set-ups costs. Two different set-up cost schemes are considered; there is either a joint set-up
cost for manufacturing and remanufacturing (single production line) or separate set-up costs
(dedicated production lines). For the joint set-up cost case, we present an exact, polynomial
time dynamic programming algorithm. For both cases, we propose a number of heuristics
and test them in an extensive numerical study.A comparison of inventory control policies for a joint manufacturing/Remanufacturing environment with remanufacturing yield loss
http://repub.eur.nl/pub/2006/
Thu, 31 Mar 2005 00:00:01 GMT<div>Z.P. Bayindir</div><div>R.H. Teunter</div><div>R. Dekker</div>
We consider a joint manufacturing / remanufacturing environment with remanufacturing yield loss. Demand and return follow independent stationary Poisson processes. Returns can be disposed off upon arrival to the system. Manufacturing and remanufacturing operations performed in the same facility at exponential rates. Yield information becomes available after remanufacturing. Demands that are not directly satisfied are lost. We investigate what inventories to consider when making production and disposal decisions, with the objective of maximizing the long-run average expected profit. Four different policies are compared that base disposal decisions on either the local (returns) inventory or the global inventory, and production decisions on either the local (serviceable) inventory or the global inventory. By modelling the system as a Markov process, expressions for the profit associated with each policy are derived. An extensive numerical study shows that it is always optimal to base disposal decisions on the local inventory and production decisions on the global inventory within the parameter sets considered. A sensitivity analysis reveals further insights.Optimise initial spare parts inventories: an analysis and improvement of an electronic decision tool.
http://repub.eur.nl/pub/1830/
Mon, 20 Dec 2004 00:00:01 GMT<div>M.E. Trimp</div><div>S.M. Sinnema</div><div>R. Dekker</div><div>R.H. Teunter</div>
Control of spare parts is very difficult as demands can be very low (once in a few years is no exception), while the consequences of a stockout can be severe. While in the past many companies choose to have very large spares inventories, one now observe trends in areas with good transportation connections to keep spare parts at the suppliers. Hence it is very important to make a good selection of which spare parts to stock at the start-up of new plants. To this end Shell Global Solutions has developed an electronic decision tool, called E-SPIR. In this report we analyse the decision rules used in it. We consider stockout penalties and advise to use criticality classifications instead. Furthermore, we investigate minimum stock levels, demand distributions and order quantities.Simple heuristics for push and pull remanufacturing policies
http://repub.eur.nl/pub/1786/
Fri, 29 Oct 2004 00:00:01 GMT<div>E.A. van der Laan</div><div>R.H. Teunter</div>
Inventory policies for joint remanufacturing and manufacturing have recently received much
attention. Most efforts, though, were related to (optimal) policy structures and numerical
optimization, rather than closed form expressions for calculating near optimal policy parameters.
The focus of this paper is on the latter. We analyze an inventory system with unit product returns and demands where remanufacturing is the cheaper alternative for manufacturing. Manufacturing is also needed, however, since there are less returns than demands. The cost structure consists of setup costs, holding costs, and backorder costs. Manufacturing and remanufacturing orders have non-zero lead times. To control the system we use certain extensions of the familiar (s,Q) policy, called push and pull remanufacturing policies. For all policies we present simple, closed form formulae for approximating the optimal policy
parameters under a cost minimization objective. In an extensive numerical study we show
that the proposed formulae lead to near-optimal policy parameters.Simple heuristics for push and pull remanufacturing policies
http://repub.eur.nl/pub/1513/
Thu, 19 Aug 2004 00:00:01 GMT<div>E.A. van der Laan</div><div>R.H. Teunter</div>
Inventory policies for joint remanufacturing and manufacturing have recently received much attention. Most efforts, though, were related to (optimal) policy structures and numerical optimization, rather than closed form expressions for calculating near optimal policy parameters. The focus of this paper is on the latter. We analyze an inventory system with unit product returns and demands where remanufacturing is the cheaper alternative for manufacturing. Manufacturing is also needed, however, since there are less returns than demands. The cost structure consists of setup costs, holding costs, and backorder costs. Manufacturing and remanufacturing orders have non-zero lead times. To control the system we use certain extensions of the familiar (s,Q) policy, called push and pull remanufacturing policies. For all policies we present simple, closed form formulae for approximating the optimal policy parameters under a cost minimization objective. In an extensive numerical study we show that the proposed formulae lead to near-optimal policy parameters.The Value of Information in Reverse Logistics
http://repub.eur.nl/pub/1447/
Fri, 06 Aug 2004 00:00:01 GMT<div>M.E. Ketzenberg</div><div>E.A. van der Laan</div><div>R.H. Teunter</div>
We explore the value of information in the context of a remanufacturer that faces uncertainty with respect to demand, product return, and product recovery (yield loss). We assume a single period model in which the operational decision of interest is the quantity of new product to order. Our objective is to evaluate the absolute and relative value of the different types of information that such a firm may choose to invest in order to reduce the uncertainty it experiences in matching supply with demand. The different types of information include demand, return, and yield loss. Our results are extensive and reveal that the value for any specific type of information depends both on the overall level of uncertainty and the level of uncertainty that is attributed to the information for which it explains. We develop and test a theoretical model that is predictive of 1) the value of each type of information, 2) the conditions that give rise to the value for each type of information, and 3) the relative value for each type of information.Inventory Strategies for Systems with Fast Remanufacturing
http://repub.eur.nl/pub/14836/
Sat, 01 May 2004 00:00:01 GMT<div>R.H. Teunter</div><div>E.A. van der Laan</div><div>D. Vlachos</div>
We describe hybrid manufacturing/remanufacturing systems with a long lead time for manufacturing and a short lead time for remanufacturing. We review the classes of inventory strategies for hybrid systems in the literature. These are all based on equal lead times. For systems with slow manufacturing and fast remanufacturing, we propose a new class. An extensive numerical experiment shows that the optimal strategy in the new class almost always performs better and often much better than the optimal strategies in all other classes.Profitability of price promotions if stockpilling increases consumption
http://repub.eur.nl/pub/1198/
Fri, 19 Mar 2004 00:00:01 GMT<div>L.H. Teunter</div><div>R.H. Teunter</div>
Price promotions induce consumers to purchase higher-than-usual
quantities, resulting in higher stocks that lead to increased
consumption. We show for a stylized model with a single shop and a
single loyal customer that because of this stockpiling effect,
promotions can be profitable even if they do not attract extra
customers.Determining optimal disassembly and recovery strategies
http://repub.eur.nl/pub/1195/
Thu, 18 Mar 2004 00:00:01 GMT<div>R.H. Teunter</div>
We present a stochastic dynamic programming algorithm for
determining the optimal disassembly and recovery strategy, given
the disassembly tree, the process dependent quality distributions
of assemblies, and the quality dependent recovery options and
associated profits for assemblies. This algorithm generalizes the
one proposed by Krikke et al. \\cite{Krikke98} in two ways. First,
there can be multiple disassembly processes. Second, partial
disassembly is allowed. Both generalizations are important for
practise.A note on "Khouja and Park, optimal lot sizing under continuous decrease, Omega 31 (2003)"
http://repub.eur.nl/pub/1184/
Tue, 09 Mar 2004 00:00:01 GMT<div>R.H. Teunter</div>
Khouja and Park (Omega 31, 539-545, 2003) analyze the problem of optimizing
the lot size under continuous price decrease. They show that the
classic EOQ formula can lead to far from optimal solutions and
develop an alternative lot size formula using the software package
Mathematica. This formula is more exact, but also more
complicated. In this note, we study the net present value
formulation of the model, and thereby gain an insight that leads
to the proposal of a modified EOQ formula. In an extensive
numerical experiment, we show that it leads to nearly optimal
solutions. It is therefore a good alternative to the formula
developed by Khouja and Park, especially if mathematical
complexity may hamper implementation.The distribution-free newsboy problem with resalable returns
http://repub.eur.nl/pub/975/
Fri, 17 Oct 2003 00:00:01 GMT<div>J. Mostard</div><div>R.H. Teunter</div><div>M.B.M. de Koster</div>
We study the case of a catalogue/internet mail order retailer selling seasonal products
and receiving large numbers of commercial returns. Returned products arriving before
the end of the selling season can be resold if there is sufficient demand. A single order
is placed before the season starts. Excess inventory at the end of the season is salvaged
and all demands not met directly are lost. Since little historical information is available,
it is impossible to determine the shape of the distribution of demand. Therefore, we
analyze the distribution-free newsboy problem with returns, in which only the mean and
variance of demand are assumed to be known. We derive a simple closed-form expression
for the distribution-free order quantity, which we compare to the optimal order quantities when
gross demand is assumed to be normal, lognormal or uniform. We find that the distribution-free
order rule performs well in most realistic cases.The multiple-job repair kit problem
http://repub.eur.nl/pub/905/
Thu, 07 Aug 2003 00:00:01 GMT<div>R.H. Teunter</div>
The repair kit problem is that of finding the optimal set of parts
in the kit of a repairman. An important aspect of this problem, in
many real-life situations, is that several job-sites are visited
before a kit is restocked. In this paper, we present two
heuristics for solving the multiple-job repair kit problem. Both
heuristics can be used to determine a solution under the
service-objective (minimal holding cost for a required job-fill
rate) as well as the cost-objective (minimal expected total cost,
including a penalty cost for each `broken' job). The `Job
Heuristic (JH)' almost always determines the exact optimal
solution, as is shown in an extensive numerical experiment.
However, it can not (easily) be used in cases where several parts
of the same type may be needed on a job, or part failures are
dependent, or the number of jobs in a tour varies. The `Part
Heuristic (PH)' is simpler and easy to use in these cases also. In
fact, it can be applied in a spreadsheet software package, as we
illustrate. The numerical experiments show that it s leads to
near-optimal solutions (average `cost error' of less than 0.1 per
cent). Therefore, the PH is an excellent method for solving repair
kit problems in practise.The newsboy problem with resalable returns
http://repub.eur.nl/pub/906/
Thu, 07 Aug 2003 00:00:01 GMT<div>J.A.M. Mostard</div><div>R.H. Teunter</div>
We analyze a newsboy problem with resalable returns. A single
order is placed before the selling season starts. Purchased
products may be returned by the customer for a full refund within
a certain time interval. Returned products are resalable, provided
they arrive back before the end of the season and are undamaged.
Products remaining at the end of the season are salvaged. All
demands not met directly are lost. We derive a simple closed-form
equation that determines the optimal order quantity given the
demand distribution, the probability that a sold product is
returned, and all relevant revenues and costs. We illustrate its
use with real data from a large catalogue/internet mail order
retailer.Lot-sizing for inventory systems with product recovery
http://repub.eur.nl/pub/907/
Thu, 07 Aug 2003 00:00:01 GMT<div>R.H. Teunter</div>
We study inventory systems with product recovery. Recovered items
are as-good-as-new and satisfy the same demands as new items. The
demand rate and return fraction are deterministic. The relevant
costs are those for ordering recovery lots, for ordering
production lots, for holding recoverable items in stock, and for
holding new/recovered items in stock. We derive simple formulae
that determine the optimal lot-sizes for the
production/procurement of new items and for the recovery of
returned items. These formulae are valid for finite and infinite
production rates as well as finite and infinite recovery rates,
and therefore more general than those in the literature.
Moreover, the method of derivation is easy and insightful.Valuation of inventories in systems with product recovery
http://repub.eur.nl/pub/908/
Thu, 07 Aug 2003 00:00:01 GMT<div>R.H. Teunter</div><div>E.A. van der Laan</div>
Valuation of inventories has different purposes, in particular
accounting and decision making, and it is not necessary for a firm
to use the same valuation method for both purposes. In fact, it is
not uncommon to use accounting books as well as management books.
In this chapter, we will only consider inventory values from the
perspective of decision making. More specifically, we will analyze
the effect of inventory valuation on inventory control decisions
(and not the corresponding financial results) for systems with
product recovery.Reverse logistics in a pharmaceutical company: a case study
http://repub.eur.nl/pub/909/
Thu, 07 Aug 2003 00:00:01 GMT<div>R.H. Teunter</div><div>K. Inderfurth</div><div>S. Minner</div><div>R. Kleber</div>
Schering spends considerable effort to undertake product recovery activities in pharmaceutical production. The two main recovery activities are by-product recycling and solvent reuse. The main driver for engaging in these activities is economical. Recovery leads to annual savings of approximately DM 25 million, which is about 8.5 % of the total production cost. This figure does not include additional savings due to reduced
disposal quantities and additional costs due to investments in recovery equipment, of which we do not have reliable estimates. Furthermore, being engaged in recovery activities has additional benefits for Schering that are related to the reduced waste stream: production is in accordance with environmental legislation, the
company builds an environmentally friendly image, and there is less strain on the environment. The downside of the recovery activities is that they complicate production and inventory planning. Especially the added complexity of production planning, resulting from cycles in the production structure, is a disadvantage.A simple MRP approach, as commonly used in practice, is no longer applicable but has to be replaced by a
more sophisticated planning procedure. Schering has developed an advanced decision support system which integrates a MIP procedure. Thus it turns out that reverse logistics also is a field which creates challenges for developing advanced planning systems in order to support practical decision making.