OASIcs, Volume 37

4th Student Conference on Operational Research



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Event

SCOR 2014, May 2-4, 2014, Nottingham, UK

Editors

Pedro Crespo Del Granado
Martim Joyce-Moniz
Stefan Ravizza

Publication Details

  • published at: 2014-08-06
  • Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
  • ISBN: 978-3-939897-67-5
  • DBLP: db/conf/scor/scor2014

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Document
Complete Volume
OASIcs, Volume 37, SCOR'14, Complete Volume

Authors: Pedro Crespo Del Granado, Martim Joyce-Moniz, and Stefan Ravizza


Abstract
OASIcs, Volume 37, SCOR'14, Complete Volume

Cite as

4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@Proceedings{crespodelgranado_et_al:OASIcs.SCOR.2014,
  title =	{{OASIcs, Volume 37, SCOR'14, Complete Volume}},
  booktitle =	{4th Student Conference on Operational Research},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014},
  URN =		{urn:nbn:de:0030-drops-46788},
  doi =		{10.4230/OASIcs.SCOR.2014},
  annote =	{Keywords: Optimization, Applications, Graph Theory, Applications, Probability and Statistics, Web-based services, Deduction and Theorem Proving}
}
Document
Front Matter
Frontmatter, Table of Contents, Preface, Conference Organization

Authors: Pedro Crespo Del Granado, Martim Joyce-Moniz, and Stefan Ravizza


Abstract
Frontmatter, Table of Contents, Preface, Conference Organization

Cite as

4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. i-xii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{crespodelgranado_et_al:OASIcs.SCOR.2014.i,
  author =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  title =	{{Frontmatter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{i--xii},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.i},
  URN =		{urn:nbn:de:0030-drops-46649},
  doi =		{10.4230/OASIcs.SCOR.2014.i},
  annote =	{Keywords: Frontmatter, Table of Contents, Preface, Conference Organization}
}
Document
A Novel Framework for Quantification of Supply Chain Risks

Authors: Abroon Qazi, John Quigley, and Alex Dickson


Abstract
Supply chain risk management is an active area of research and there is a research gap of exploring established risk quantification techniques in other fields for application in the context of supply chain management. We have developed a novel framework for quantification of supply chain risks that integrates two techniques of Bayesian belief network and Game theory. Bayesian belief network can capture interdependency between risk factors and Game theory can assess risks associated with conflicting incentives of stakeholders within a supply network. We introduce a new node termed ‘Game theoretic risks’ in Bayesian network that gets its qualitative and quantitative structure from the Game theory based analysis of the existing policies and partnerships within a supply network. We have applied our proposed risk modeling framework on the development project of Boeing 787 aircraft. Two different Bayesian networks have been modeled; one representing the Boeing’s perceived supply chain risks and the other depicting real time supply chain risks faced by the company. The qualitative structures of both the models were developed through cognitive maps that were constructed from the facts outlined in a case study. The quantitative parts were populated based on intuition and subsequently updated with the facts. The Bayesian network model incorporating quantification of game theoretic risks provides all the reasons for the delays and financial loss of the project. Furthermore, the proactive strategies identified in various case studies were verified through our model. Such an integrated application of two different quantification techniques in the realm of supply chain risk management bridges the mentioned research gap. Successful application of the framework justifies its potential for further testing in other supply chain risk quantification scenarios.

Cite as

Abroon Qazi, John Quigley, and Alex Dickson. A Novel Framework for Quantification of Supply Chain Risks. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{qazi_et_al:OASIcs.SCOR.2014.1,
  author =	{Qazi, Abroon and Quigley, John and Dickson, Alex},
  title =	{{A Novel Framework for Quantification of Supply Chain Risks}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{1--15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.1},
  URN =		{urn:nbn:de:0030-drops-46653},
  doi =		{10.4230/OASIcs.SCOR.2014.1},
  annote =	{Keywords: bayesian belief network, cognitive maps, conflicting incentives, game theory, supply chain risk management}
}
Document
Multilingual Trend Detection in the Web

Authors: Jan Stutzki


Abstract
This paper represents results from our ongoing research project in the foresight area. The goal of the project is to develop web based tools which automatically detect activity and trends regarding given keywords. This knowledge can be used to enable decision makers to react proactively to arising challenges. As for now we can detect trends worldwide in more than 60 languages and assign these trends accordingly to over 100 national states. To reach this goal we utilize the big search engines as their core competence is to determine the relevance of a document regarding the search query. The search engines allow slicing of the results by language and country. In the next step we download some of the proposed documents for analysis. Because of the amount of information required we reach the field of Big Data. Therefore an extra effort is made to ensure scalability of the application. We introduce a new approach to activity and trend detection by combining the data collection and detection methods. To finally detect trends in the gathered data we use data mining methods which allow us to be independent from the language a document is written in. The input of these methods is the text data of the downloaded documents and a specially prepared index structure containing meta data and various other information which accumulate during the collection of the documents. We show that we can reliably detect trends and activities in highly active topics and discuss future research.

Cite as

Jan Stutzki. Multilingual Trend Detection in the Web. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 16-24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{stutzki:OASIcs.SCOR.2014.16,
  author =	{Stutzki, Jan},
  title =	{{Multilingual Trend Detection in the Web}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{16--24},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.16},
  URN =		{urn:nbn:de:0030-drops-46663},
  doi =		{10.4230/OASIcs.SCOR.2014.16},
  annote =	{Keywords: Information Retrieval, Web Mining, Trend Detection}
}
Document
Solving the p-median location problem with the Erlenkotter approach in public service system design

Authors: Ján Bendík


Abstract
The problem can be often formulated as a weighted p-median problem. Real instances of the problem are characterized by big numbers of possible service center locations, which can take the value of several hundreds or thousands. The optimal solution can be obtained by the universal IP solvers only for smaller instances of the problem. The universal IP solvers are very time-consuming and often fail when solving a large instance. Our approach to the problem is based on the Erlenkotter procedure for solving of the uncapacitated facility location problem and on the Lagrangean relaxation of the constraint which limits number of the located center. The suggested approach finds the optimal solution in most of the studied instances. The quality and the feasibility of the resulting solutions of the suggested approach depend on the setting of the Lagrangean multiplier. A suitable value of the multiplier can be obtained by a bisection algorithm. The resulting multiplier cannot guarantee an optimal solution, but provides a near-to-optimal solution and a lower bound. If our approach does not obtain the optimal solution, then a heuristic improves the near-to-optimal solution. The resulting solution of our approach and the optimal solution obtained by the universal IP solver XPRESS-IVE are compared in the computational time and the quality of solutions.

Cite as

Ján Bendík. Solving the p-median location problem with the Erlenkotter approach in public service system design. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 25-33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{bendik:OASIcs.SCOR.2014.25,
  author =	{Bend{\'\i}k, J\'{a}n},
  title =	{{Solving the p-median location problem with the Erlenkotter approach in public service system design}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{25--33},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.25},
  URN =		{urn:nbn:de:0030-drops-46676},
  doi =		{10.4230/OASIcs.SCOR.2014.25},
  annote =	{Keywords: p-median location problem, Erlenkotter's approach, Lagrangean relaxation}
}
Document
A new approach to modelling nonlinear time series: Introducing the ExpAR-ARCH and ExpAR-GARCH models and applications

Authors: Paraskevi Katsiampa


Abstract
The analysis of time series has long been the subject of interest in different fields. For decades time series were analysed with linear models. Nevertheless, an issue that has been raised is whether there exist other models that can explain and fit real data better than linear ones. In this paper, new nonlinear time series models are proposed (namely the ExpAR-ARCH and the ExpAR-GARCH), which are combinations of a nonlinear model in the conditional mean and a nonlinear model in the conditional variance and have the potential of explaining observed data in various fields. Simulated data of these models are presented, while different algorithms (the Nelder-Mead simplex direct search method, the Quasi-Newton line search algorithm, the Active-Set algorithm, the Sequential Quadratic Programming algorithm, the Interior Point algorithm and a Genetic Algorithm) are used and compared in order to check their estimation performance when it comes to these suggested nonlinear models. Moreover, an application to the Dow Jones data is considered, showing that the new models can explain real data better than the AR-ARCH and AR-GARCH models.

Cite as

Paraskevi Katsiampa. A new approach to modelling nonlinear time series: Introducing the ExpAR-ARCH and ExpAR-GARCH models and applications. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 34-51, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{katsiampa:OASIcs.SCOR.2014.34,
  author =	{Katsiampa, Paraskevi},
  title =	{{A new approach to modelling nonlinear time series: Introducing the ExpAR-ARCH and ExpAR-GARCH models and applications}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{34--51},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.34},
  URN =		{urn:nbn:de:0030-drops-46683},
  doi =		{10.4230/OASIcs.SCOR.2014.34},
  annote =	{Keywords: Nonlinear time series, ExpAR-ARCH model, ExpAR-GARCH model}
}
Document
Coordinating push and pull flows in a lost sales stochastic supply chain

Authors: Georgios Varlas and Michael Vidalis


Abstract
In this paper a serial, three echelon, push-pull supply chain is investigated. The supply chain consists of a provider, a distribution centre (buffer) and a retailer. The material flow between upstream stages is push type, while between downstream stages it is driven by continuous review, reorder point/order quantity inventory control policy. Exponentially distributed lead times between stages are assumed. External demand occurs according to pure Poisson, while the demand that cannot be met is lost. The system is modelled using matrix analytic methods as a Markov birth-and-death process. An algorithm is developed to generate the transition matrix for different parameters of the system. Then, the corresponding system of stationary linear equations is generated and the solution of the stationary probabilities is provided. Key performance metrics such as average inventories and customer service levels at each echelon of the system can be computed. The algorithm is programmed in Matlab© and its validity is tested using simulation, with the two approaches giving practically identical results. The contribution of our work is an exact algorithm for a lost sales push-pull supply network. This algorithm can be used to evaluate different scenarios for supply chain design, to explore the dynamics of a push-pull system, or as an optimization tool.

Cite as

Georgios Varlas and Michael Vidalis. Coordinating push and pull flows in a lost sales stochastic supply chain. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 52-62, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{varlas_et_al:OASIcs.SCOR.2014.52,
  author =	{Varlas, Georgios and Vidalis, Michael},
  title =	{{Coordinating push and pull flows in a lost sales stochastic supply chain}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{52--62},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.52},
  URN =		{urn:nbn:de:0030-drops-46698},
  doi =		{10.4230/OASIcs.SCOR.2014.52},
  annote =	{Keywords: Supply Chain Management, Push-Pull systems, Markov Processes}
}
Document
Mathematical Programming bounds for Large-Scale Unit Commitment Problems in Medium-Term Energy System Simulations

Authors: Alberto Ceselli, Alberto Gelmini, Giovanni Righini, and Andrea Taverna


Abstract
We consider a large-scale unit commitment problem arising in medium-term simulation of energy networks, stemming from a joint project between the University of Milan and a major energy research centre in Italy. Optimal plans must be computed for a set of thermal and hydroelectric power plants, located in one or more countries, over a time horizon spanning from a few months to one year, with a hour-by-hour resolution. We propose a mixed-integer linear programming model for the problem. Since the complexity of this unit commitment problem and the size of real-world instances make it impractical to directly optimise this model using general purpose solvers, we devise ad-hoc heuristics and relaxations to obtain approximated solutions and quality estimations. We exploit an incremental approach: at first, a linear relaxation of an aggregated model is solved. Then, the model is disaggregated and the full linear relaxation is computed. Finally, a tighter linear relaxation of an extended formulation is obtained using column generation. At each stage, metaheuristics are run to obtain good integer solutions. Experimental tests on real-world data reveal that accurate results can be obtained by our framework in affordable time, making it suitable for efficient scenario simulations.

Cite as

Alberto Ceselli, Alberto Gelmini, Giovanni Righini, and Andrea Taverna. Mathematical Programming bounds for Large-Scale Unit Commitment Problems in Medium-Term Energy System Simulations. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 63-75, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{ceselli_et_al:OASIcs.SCOR.2014.63,
  author =	{Ceselli, Alberto and Gelmini, Alberto and Righini, Giovanni and Taverna, Andrea},
  title =	{{Mathematical Programming bounds for Large-Scale Unit Commitment Problems in Medium-Term Energy System Simulations}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{63--75},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.63},
  URN =		{urn:nbn:de:0030-drops-46704},
  doi =		{10.4230/OASIcs.SCOR.2014.63},
  annote =	{Keywords: mathematical programming, unit commitment, power systems}
}
Document
A Model-Based Heuristic to the Min Max K-Arc Routing for Connectivity Problem

Authors: Vahid Akbari and Sibel Salman


Abstract
We consider the post-disaster road clearing problem with the goal of restoring network connectivity in shortest time. Given a set of blocked edges in the road network, teams positioned at depot nodes are dispatched to open a subset of them that reconnects the network. After a team finishes working on an edge, others can traverse it. The problem is to find coordinated routes for the teams. We generate a feasible solution using a constructive heuristic algorithm after solving a relaxed mixed integer program. In almost 70 percent of the instances generated both randomly and from Istanbul data, the relaxation solution turned out to be feasible, i.e. optimal for the original problem.

Cite as

Vahid Akbari and Sibel Salman. A Model-Based Heuristic to the Min Max K-Arc Routing for Connectivity Problem. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 76-88, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{akbari_et_al:OASIcs.SCOR.2014.76,
  author =	{Akbari, Vahid and Salman, Sibel},
  title =	{{A Model-Based Heuristic to the Min Max K-Arc Routing for Connectivity Problem}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{76--88},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.76},
  URN =		{urn:nbn:de:0030-drops-46714},
  doi =		{10.4230/OASIcs.SCOR.2014.76},
  annote =	{Keywords: Arc Routing Problem, Mixed Integer Programming, Heuristic, Network Connectivity, Road Clearance}
}
Document
A Review of Dynamic Bayesian Network Techniques with Applications in Healthcare Risk Modelling

Authors: Mohsen Mesgarpour, Thierry Chaussalet, and Salma Chahed


Abstract
Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

Cite as

Mohsen Mesgarpour, Thierry Chaussalet, and Salma Chahed. A Review of Dynamic Bayesian Network Techniques with Applications in Healthcare Risk Modelling. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 89-100, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{mesgarpour_et_al:OASIcs.SCOR.2014.89,
  author =	{Mesgarpour, Mohsen and Chaussalet, Thierry and Chahed, Salma},
  title =	{{A Review of Dynamic Bayesian Network Techniques with Applications in Healthcare Risk Modelling}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{89--100},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.89},
  URN =		{urn:nbn:de:0030-drops-46727},
  doi =		{10.4230/OASIcs.SCOR.2014.89},
  annote =	{Keywords: Healthcare Modelling, Dynamic Bayesian Network, Predictive Risk Modelling, Time-Varying, Hospital Administrative Data}
}
Document
Demand models for the static retail price optimization problem - A Revenue Management perspective

Authors: Timo P. Kunz and Sven F. Crone


Abstract
Revenue Management (RM) has been successfully applied to many industries and to various problem settings. While this is well reflected in research, RM literature is almost entirely focused on the dynamic pricing problem where a perishable product is priced over a finite selling horizon. In retail however, the static case, in which products are continuously replenished and therefore virtually imperishable is equally relevant and features a unique set of industry-specific problem properties. Different aspects of this problem have been discussed in isolation in various fields. The relevant contributions remain therefore scattered throughout Operations Research, Econometrics, and foremost Marketing and Retailing while a holistic discussion is virtually non-existent. We argue that RM with its interdisciplinary, practical, and systemic approach would provide the ideal framework to connect relevant research across fields and to narrow the gap between theory and practice. We present a review of the static retail pricing problem from an RM perspective in which we focus on the demand model as the core of the retail RM system and highlight its links to the data and the optimization model. We then define five criteria that we consider critical for the applicability of the demand model in the retail RM context. We discuss the relevant models in the light of these criteria and review literature that has connected different aspects of the problem. We identify several avenues for future research to illustrate the vast potential of discussing the static retail pricing problem in the RM context.

Cite as

Timo P. Kunz and Sven F. Crone. Demand models for the static retail price optimization problem - A Revenue Management perspective. In 4th Student Conference on Operational Research. Open Access Series in Informatics (OASIcs), Volume 37, pp. 101-125, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{kunz_et_al:OASIcs.SCOR.2014.101,
  author =	{Kunz, Timo P. and Crone, Sven F.},
  title =	{{Demand models for the static retail price optimization problem - A Revenue Management perspective}},
  booktitle =	{4th Student Conference on Operational Research},
  pages =	{101--125},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-67-5},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{37},
  editor =	{Crespo Del Granado, Pedro and Joyce-Moniz, Martim and Ravizza, Stefan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2014.101},
  URN =		{urn:nbn:de:0030-drops-46739},
  doi =		{10.4230/OASIcs.SCOR.2014.101},
  annote =	{Keywords: Revenue Management, Pricing, Retail, Demand Modeling}
}

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