Sandra (A.C.C.) van Wijk
Sandra van Wijk is a visiting assistant professor in Supply Chain Management at American University of Sharjah (Sharjah, UAE) in the Department of Marketing and Information Systems of the School of Business Administration. She is teaching courses on supply chain management, operations management, logistics, and managerial statistics, both in the undergraduate program and in the MBA program.
Sandra's research interests focus on stochastic operations research, supply chain and inventory management, performance analysis of stochastic systems, sustainable operations, and queueing theory.
Before, she was a Postdoctoral Research Fellow at McGill University (Montreal, Canada), Desautels Faculty of Management, working on sustainable operations and closed-loop supply chain management. Also, she held positions as Postdoctoral Researcher at Qatar University (Doha, Qatar), and at the Hamilton Institute (National University of Ireland Maynooth, Maynooth, Ireland).
In 2012, she received her PhD from Eindhoven University of Technology. She worked on the 'Creation of Pooling in Inventory and Queueing Models', resulting in her thesis "Pooling and Polling" (see http://tue.academia.edu/SandraVanWijk/Books). She mainly investigates the efficient use of scarce resources, such as inventory or server capacity. One of the main focuses is the use of lateral transshipments in spare parts inventory models, in this way pooling the inventory between multiple warehouses. Also, she studied the pooling of servers in queueing models. Next to this, she worked on polling models, which are queueing models where multiple queues are served by a single server.
Her PhD research was a joint project of the Mathematics department (Stochastic Operational Research group) and the School of Industrial Engineering (Operations, Planning, Accounting, and Control group). Furthermore, she worked at research institute EURANDOM (Queueing and Performance Analysis track). Her thesis advisors were dr. Ivo Adan and dr. Geert-Jan van Houtum, while she also worked with dr. Onno Boxma and dr. Ton de Kok.
In 2012, she received a Prince Bernhard Scholarship for visiting the computer science department of Carnegie Mellon University (CMU, Pittsburgh, PA, USA), working together with Mor Harchol-Balter and Alan Scheller-Wolf.
Sandra graduated from Eindhoven University of Technology in Industrial and Applied Mathematics (BSc 2006, MSc 2007, PhD 2012). Previously, she worked as a mathematics teacher in high schools, teaching assistant at university, and conducted internships in the Stochastic Operational Research group of Eindhoven University of Technology and at Philips Research Eindhoven.
Supervisors: A.G. de Kok, O.J. Boxma, I.J.B.F. Adan, and G.J. van Houtum
Address: American University of Sharjah,
School of Business Administration,
Department of Marketing and Information Systems,
PO Box 26666,
Sharjah,
UAE
Sandra's research interests focus on stochastic operations research, supply chain and inventory management, performance analysis of stochastic systems, sustainable operations, and queueing theory.
Before, she was a Postdoctoral Research Fellow at McGill University (Montreal, Canada), Desautels Faculty of Management, working on sustainable operations and closed-loop supply chain management. Also, she held positions as Postdoctoral Researcher at Qatar University (Doha, Qatar), and at the Hamilton Institute (National University of Ireland Maynooth, Maynooth, Ireland).
In 2012, she received her PhD from Eindhoven University of Technology. She worked on the 'Creation of Pooling in Inventory and Queueing Models', resulting in her thesis "Pooling and Polling" (see http://tue.academia.edu/SandraVanWijk/Books). She mainly investigates the efficient use of scarce resources, such as inventory or server capacity. One of the main focuses is the use of lateral transshipments in spare parts inventory models, in this way pooling the inventory between multiple warehouses. Also, she studied the pooling of servers in queueing models. Next to this, she worked on polling models, which are queueing models where multiple queues are served by a single server.
Her PhD research was a joint project of the Mathematics department (Stochastic Operational Research group) and the School of Industrial Engineering (Operations, Planning, Accounting, and Control group). Furthermore, she worked at research institute EURANDOM (Queueing and Performance Analysis track). Her thesis advisors were dr. Ivo Adan and dr. Geert-Jan van Houtum, while she also worked with dr. Onno Boxma and dr. Ton de Kok.
In 2012, she received a Prince Bernhard Scholarship for visiting the computer science department of Carnegie Mellon University (CMU, Pittsburgh, PA, USA), working together with Mor Harchol-Balter and Alan Scheller-Wolf.
Sandra graduated from Eindhoven University of Technology in Industrial and Applied Mathematics (BSc 2006, MSc 2007, PhD 2012). Previously, she worked as a mathematics teacher in high schools, teaching assistant at university, and conducted internships in the Stochastic Operational Research group of Eindhoven University of Technology and at Philips Research Eindhoven.
Supervisors: A.G. de Kok, O.J. Boxma, I.J.B.F. Adan, and G.J. van Houtum
Address: American University of Sharjah,
School of Business Administration,
Department of Marketing and Information Systems,
PO Box 26666,
Sharjah,
UAE
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Books by Sandra (A.C.C.) van Wijk
This monograph consists of two parts: pooling and polling . In the first part, 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, in the first part, 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 closed-form 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 k-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.
Slides of presentation during PhD defense: http://tue.academia.edu/SandraVanWijk/Talks/82570/Pooling_and_Polling_Creation_of_Pooling_in_Inventory_and_Queueing_Models
Papers by Sandra (A.C.C.) van Wijk
This monograph consists of two parts: pooling and polling . In the first part, 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, in the first part, 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 closed-form 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 k-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.
Slides of presentation during PhD defense: http://tue.academia.edu/SandraVanWijk/Talks/82570/Pooling_and_Polling_Creation_of_Pooling_in_Inventory_and_Queueing_Models
Slides (updated) available via: http://www.academia.edu/attachments/9891037/download_file.
In previous research, we solved the two location problem, for which we completely characterized the structure of the optimal policy. We derived conditions under which simple, easy to implement, policies are always optimal. Furthermore, we identifed the parameter settings under which one can gain most from lateral transshipments. Currently, we are focusing on multi-location models, with more than two stock points. For a special case, where only one stock point issues lateral transshipments, we characterized the optimal policy structures. However, our current techniques do not straightforwardly generalize to the general multi-location model. Hence, we have to restrict the possibilities for stock transfers in our model. Firstly, we only allow lateral transshipments when a location is stocked-out, although this can be suboptimal in the two location model. Secondly, we probably have to limit or restrict the transshipments between the stock points.
For this model, we want to prove that a so-called hold back pooling strategy is optimal. In this case a stock point can hold it last part(s) back from a lateral transshipment, which is determined by its hold back level. Then, we want to gain insights in the optimal settings of these hold back levels. That is, we want to optimize the lateral transshipment policy within the class of hold back policies. Moreover, from an implementation point of view, such a simple, parameterized policy may be much more attractive than an overall optimal policy. Furthermore, we investigate the gap between the optimal hold back policy and the overall optimal policy.
For this, we studied a system with two stock points, for which we completely characterized the structure of the optimal policy. We derived conditions under which simple, easy to implement, policies are always optimal. Furthermore, we identified the parameter settings under which one can gain most from lateral transshipments. For more than two stock points, we characterized the optimal policy structure for a system where only one stock point issues lateral transshipments. Moreover, we constructed an approximation algorithm for the general multi- location setting, determining the performance when executing a given policy. This can also be used for the optimization of parameters within a given class of policies, as from an implementation point of view, a simple parameterized policy may be much more attractive than an overall optimal policy. Furthermore, we investigated the gap between the optimal policy within a given class of parameterized policies and the overall optimal policy.