A.F. Gabor (Adriana)
http://repub.eur.nl/ppl/19062/
List of Publicationsenhttp://repub.eur.nl/logo.jpg
http://repub.eur.nl/
RePub, Erasmus University RepositoryComparison of two methods for customer differentiation
http://repub.eur.nl/pub/50502/
Sat, 15 Feb 2014 00:00:01 GMT<div>A.F. Gabor</div><div>Y. Guang</div><div>S. Axsäter</div>
In response to customer specific time guarantee requirements, service providers can offer differentiated ser- vices. However, conventional customer differentiation methods often lead to high holding costs and may have some practical drawbacks. We compare two customer differentiation policies: stock reservation and pipeline stock priority for high priority customers. We derive exact analytical expressions of the waiting time distri- bution of both types of customers for a stock reservation policy. We then provide accurate approximation methods for a pipeline stock priority policy. By comparison, we offer insights concerning which method should be used under different service level requirements.Approximating Order-up-to Policies for Inventory Systems with Binomial Yield
http://repub.eur.nl/pub/50579/
Wed, 01 Jan 2014 00:00:01 GMT<div>W. Ju</div><div>A.F. Gabor</div><div>J.C.W. van Ommeren</div>
__Abstract__
This paper studies an inventory policy for a retailer who orders his products
from a supplier whose deliveries only partially satisfy the quality requirements.
We model this situation by an innite-horizon periodic-review model
with binomial random yield and positive lead time. We propose an orderup-
to policy based on approximating the inventory model with unreliable
supplier by a model with a reliable supplier and suitably modied demand
distribution. The performance of the order-up-to policy is veried by comparing
it with both the optimal policy and the safety stock policy proposed
in Inderfurth & Vogelgesang (2013). Further, we extend our approximation
to a dual-sourcing model with two suppliers: the rst slow and unreliable,
and the other fast and fully reliable. Compared to the dual-index orderup-
to policy for the model with full information on the yield, the proposed approximation gives promising results.Approximate Order-up-to Policies for Inventory Systems with Binomial Yield
http://repub.eur.nl/pub/50255/
Tue, 31 Dec 2013 00:00:01 GMT<div>W. Ju</div><div>A.F. Gabor</div><div>J.C.W. van Ommeren</div>
This paper studies an inventory policy for a retailer who orders his products from a supplier whose deliveries only partially satisfy the quality require- ments. We model this situation by an infinite-horizon periodic-review model with binomial random yield and positive lead time. We propose an order- up-to policy based on approximating the inventory model with unreliable supplier by a model with a reliable supplier and suitably modified demand distribution. The performance of the order-up-to policy is verified by com- paring it with both the optimal policy and the safety stock policy proposed in Inderfurth & Vogelgesang (2013). Further, we extend our approximation to a dual-sourcing model with two suppliers: the first slow and unreliable, and the other fast and fully reliable. Compared to the dual-index order- up-to policy for the model with full information on the yield, the proposed approximation gives promising results.Service parts inventory control with lateral transshipment and pipeline stockflexibility
http://repub.eur.nl/pub/39187/
Mon, 01 Apr 2013 00:00:01 GMT<div>G. Yang</div><div>R. Dekker</div><div>A.F. Gabor</div><div>S. Axsäter</div>
In equipment-intensive industries such as truck, electronics, aircraft and dredging vessel manufacturing, service parts are often slow moving items for which the transshipment time is not negligible. However, this aspect is hardly considered in the existing service logistics literature. In this paper, we consider this aspect and propose a customer-oriented service measure which takes into account pipeline stock and lateral transshipment flexibility. We provide an approximation method for optimizing the stock allocation subject to this service measure. Via extensive numerical experiments, we show that our approximation performs very well with respect to both system performance and costs. Moreover, our numerical experiments indicate that including lateral transshipments and pipeline stock flexibility in inventory decisions is more beneficial than lateral transshipments alone. This effect is larger for high demand rates and high lateral transshipment costs. Results from a case study in the dredging industry confirm our findings. We therefore recommend introduction of pipeline stock information such as the track and trace information from freight carriers in existing ERP systems. The Time Window Assignment Vehicle Routing Problem
http://repub.eur.nl/pub/32175/
Sun, 01 Apr 2012 00:00:01 GMT<div>R. Spliet</div><div>A.F. Gabor</div>
In many distribution networks, it is vital that time windows in which deliveries are made are assigned to customers for the long term. However, at the moment of assigning time windows demand is not known. In this paper we introduce the time window assignment vehicle routing problem, the TWAVRP. In this problem time windows have to be assigned before demand is known. Next the realization of demand is revealed and an optimal vehicle routing schedule has to be made that satisfies the time window constraints. We assume that different scenarios of demand realizations are known, as well as their probability distribution. The TWAVRP is the problem of assigning time windows such that the expected traveling costs are minimized. We propose a formulation of the TWAVRP and develop two variants of a column generation algorithm to solve the LP relaxation of this formulation. Numerical experiments show that these algorithms provide us with very tight LP-bounds to instances of moderate size in reasonable computation time. We incorporate the column generation algorithm in a branch and price algorithm and find optimal integer solutions to small instances of the TWAVRP. In our numerical experiments, the branch and price algorithm typically finds the optimal solution very early in the branching procedure and spends most time on proving optimality.Maximizing revenue with allocation of multiple advertisements on a Web banner
http://repub.eur.nl/pub/22995/
Sat, 01 Oct 2011 00:00:01 GMT<div>V. Boskamp</div><div>A. Knoops</div><div>F. Frasincar</div><div>A.F. Gabor</div>
The problem addressed in this paper is the allocation of multiple advertisements on a Web banner, in order to maximize the revenue of the allocated advertisements. It is essentially a two-dimensional, single, orthogonal, knapsack problem, applied to pixel advertisement. As this problem is known to be NP-hard, and due to the temporal constraints that Web applications need to fulfill, we propose several heuristic algorithms for generating allocation patterns. The heuristic algorithms presented in this paper are the left justified algorithm, the orthogonal algorithm, the GRASP constructive algorithm, and the greedy stripping algorithm. We set out an experimental design using standard banner sizes, and primary and secondary sorting criteria for the set of advertisements. We run two simulations, the first simulation compares the heuristics with an optimal solution found using brute force search, and the second simulation compares the heuristic algorithms to gain a better insight into their performance. Finding a suitable pattern generating algorithm is a trade-off between effectiveness and efficiency. Results indicate that allocating advertisements with the orthogonal algorithm is the most effective. In contrast, allocating advertisements using the greedy stripping algorithm is the most efficient. Furthermore, the best settings per algorithm for each banner size are given.A Local Search Algorithm for Clustering in Software as a Service Networks
http://repub.eur.nl/pub/22723/
Wed, 02 Mar 2011 00:00:01 GMT<div>J.P. van der Gaast</div><div>C.A. Rietveld</div><div>A.F. Gabor</div><div>Y. Zhang</div>
In this paper we present and analyze a model for clustering in networks that offer Software as a Service (SaaS). In this problem, organizations requesting a set of applications have to be assigned to clusters such that the costs of opening clusters and installing the necessary applications in clusters are minimized. We prove that this problem is NP-hard, and model it as an Integer Program with symmetry breaking constraints. We then propose a Tabu search heuristic for situations where good solutions are desired in a short computation time. Extensive computational experiments are conducted for evaluating the quality of the solutions obtained by the IP model and the Tabu Search heuristic. Experimental results indicate that the proposed Tabu Search is promising.Maximizing revenue with allocation of multiple advertisements on a Web banner
http://repub.eur.nl/pub/22753/
Sat, 01 Jan 2011 00:00:01 GMT<div>V. Boskamp</div><div>A. Knoops</div><div>F. Frasincar</div><div>A.F. Gabor</div>
The problem addressed in this paper is the allocation of multiple advertisements on a Web banner, in order to maximize the revenue of the allocated advertisements. It is essentially a two-dimensional, single, orthogonal, knapsack problem, applied to pixel advertisement. As this problem is known to be NP-hard, and due to the temporal constraints that Web applications need to fulfill, we propose several heuristic algorithms for generating allocation patterns. The heuristic algorithms presented in this paper are the left justified algorithm, the orthogonal algorithm, the GRASP constructive algorithm, and the greedy stripping algorithm. We set out an experimental design using standard banner sizes, and primary and secondary sorting criteria for the set of advertisements. We run two simulations, the first simulation compares the heuristics with an optimal solution found using brute force search, and the second simulation compares the heuristic algorithms to gain a better insight into their performance. Finding a suitable pattern generating algorithm is a trade-off between effectiveness and efficiency. Results indicate that allocating advertisements with the orthogonal algorithm is the most effective. In contrast, allocating advertisements using the greedy stripping algorithm is the most efficient. Furthermore, the best settings per algorithm for each banner size are given.How *not* to solve a Sudoku
http://repub.eur.nl/pub/22168/
Mon, 01 Nov 2010 00:00:01 GMT<div>A.F. Gabor</div><div>G.J. Woeginger</div>
We prove the NP-hardness of a consistency checking problem that arises in certain elimination strategies for solving Sudoku-type problems.An approximation algorithm for the k-level stochastic facility location problem
http://repub.eur.nl/pub/19665/
Wed, 01 Sep 2010 00:00:01 GMT<div>Z. Wang</div><div>D. Du</div><div>A.F. Gabor</div><div>D. Xu</div>
We consider the k-level stochastic facility location problem. For this, we present an LP rounding algorithm that is 3-approximate. This result is achieved by a novel integer linear programming formulation that exploits the stochastic structure.A new approximation algorithm for the multilevel facility location problem
http://repub.eur.nl/pub/18217/
Sat, 06 Mar 2010 00:00:01 GMT<div>A.F. Gabor</div><div>J.C.W. van Ommeren</div>
In this paper we propose a new integer programming formulation for the multilevel facility location problem and a novel 3-approximation algorithm based on LP-rounding. The linear program that we use has a polynomial number of variables and constraints, thus being more efficient than the one commonly used in the approximation algorithms for these types of problems.The Vehicle Rescheduling Problem
http://repub.eur.nl/pub/17350/
Thu, 26 Nov 2009 00:00:01 GMT<div>R. Spliet</div><div>A.F. Gabor</div><div>R. Dekker</div>
The capacitated vehicle routing problem is to find a routing schedule describing the order in which geographically dispersed customers are visited to satisfy demand by supplying goods stored at the depot, such that the traveling costs are minimized. In many practical applications, a long term routing schedule has to be made for operational purposes, often based on average demand estimates. When demand substantially differs, constructing a new schedule is beneficial. The vehicle rescheduling problem is to find a new schedule that not only minimizes the total traveling costs but also minimizes the costs of deviating from the original schedule. In this paper two mathematical programming formulations of the rescheduling problem are presented as well as two heuristic methods, a two-phase heuristic and a modified savings heuristic. Computational and analytical results show that for sufficiently high deviation costs, the two-phase heuristic generates a schedule that is on average close to optimal or even guaranteed optimal, for all considered problem instances. The modified savings heuristic generates schedules of constant quality, however the two-phase heuristic produces schedules that are on average closer to the optimum.Admission control for differentiated services in future generation CDMA networks
http://repub.eur.nl/pub/16069/
Tue, 01 Sep 2009 00:00:01 GMT<div>H.P. Tan</div><div>R. Núñez-Queija</div><div>A.F. Gabor</div><div>O.J. Boxma</div>
Future Generation CDMA wireless systems, e.g., 3G, can simultaneously accommodate flow transmissions of users with widely heterogeneous applications. As radio resources are limited, we propose an admission control rule that protects users with stringent transmission bit-rate requirements ("streaming traffic") while offering sufficient capacity over longer time intervals to delay-tolerant users ("elastic traffic"). While our strategy may not satisfy classical notions of fairness, we aim to reduce congestion and increase overall throughput of elastic users. Using time-scale decomposition, we develop approximations to evaluate the performance of our differentiated admission control strategy to support integrated services with transmission bit-rate requirements in a realistic downlink transmission scenario for a single radio cell.Scheduling deliveries under uncertainty
http://repub.eur.nl/pub/16236/
Thu, 25 Jun 2009 00:00:01 GMT<div>A.F. Gabor</div><div>R. Dekker</div><div>T. van Dijk</div><div>P. van Scheepstal</div>
Quite often transportation companies face two types of jobs, ones which they can plan themselves and ones which have to be done on call. In this paper we study the scheduling of these jobs, while we assume that job durations are known beforehand as well as windows in which the jobs need to be done. We develop several heuristics to solve the problem at hand. The most successful are based on defining an appropriate buffer. The methods are assessed in extensive experiments on two aspects, viz. efficiency, in the sense that they carry out many jobs and certainty, in the sense that they provide information beforehand about which jobs they will execute.