Seminars in Operational Research 2009

Venue H10-31, time 15:30h.

Feb. 13

Cerag  Pince (Erasmus University Rotterdam, Econometric Institute)


Excess Stock Removal Problem for a Continuous Review Inventory System

We consider a single item, single location, continuous review inventory system when the demand rate jumps to a lower level at a specific time point in the future. The timing of the shift, the current demand rate and the final demand rate are assumed to be known. The adaptation to the new inventory position is achieved by letting the demand process take away the excess stocks. The main contribution of our work lies in the explicit modeling of prior action for adjusting to the new inventory position dictated by the change in demand rate.

Mei 13

Yingqian Zhang (TU Delft)


Mechanism design for multi-agent planning: difficulties and possibilities

This talk will start with a general overview on the subject of algorithmic mechanism design, and then focus on one specific topic of applying mechanism design to multi-agent planning. Multi-agent planning methods are concerned with planning by and for a group of agents. If the agents are self-interested, they may be tempted to lie in order to obtain an outcome that is more rewarding for them. We therefore study the multi-agent planning problem from a mechanism design perspective, showing how to incentivise agents to be truthful. We prove that the well-known truthful VCG mechanism is not always truthful in the context of optimal planning, and present a modification to fix this. We then present some (domain-dependent) polynomial-time planning algorithms using this fix that maintain truthfulness in spite of their non-optimality.

Venue: 16:00-17:00h
Location: H10-31

June 12

Willem van Jaarsveld (Erasmus Universiteit Rotterdam)


On the heuristics for optimizing the rationing levels in the (S-1, S) lost sales inventory model with multiple demand classes

We examine the heuristics proposed by Kranenburg and van Houtum (2007) for finding good rationing policies in the (S,S-1) lost sales inventory model with multiple demand classes. Our main result is that we establish guaranteed optimality for two of these heuristics. As a corollary, we provide an alternative proof for the optimality of rationing policies among the class of all policies.

Venue: 12:00-13:00h
Location: H10-31

June 26

Ruth Carrasco-Gallego (School of Industrial Engineering of the Technical University of Madrid (UPM))


A management model for reuse closed-loop supply chains. Scheduling of replenishment orders in the piece picking area of a warehouse

This seminar will be split in two presentations. First, we put forward a framework for reuse closed-loop supply chains. This conceptual model is grounded in a set of case studies and has been contrasted with existing literature. The main contribution of our work lies in the simultaneous consideration of different types of reusable articles (returnable transportation items, returnable primary packaging materials, products that are used multiple times) and the identification of the major issues arising in the management of these systems.

Second, we address the replenishment of the piece picking area in a warehouse. The productivity of broken-case picking operations can be increased by splitting an SKU inventory in a forward area (piece picking) and a reserve area (storage), although, on the other hand, this requires regular replenishments from one area to the other. The forward-reserve problem (FRP) is used to decide which products and in what quantities are to be stored in the forward area, so that the total cost of order picking and replenishment is minimized. A variant of the VRP and the TSP are used to batch picking orders and optimize picking paths. The possibility of stockouts in the picking racks is not considered, although they occur in industrial practice. We propose a procedure for scheduling forward area replenishment orders aiming at the reduction of stockout probability.

Venue: 12:00-13:00h
Location: H10-31

July 10

Soheil Sibdari (Charlton College of Business, University of Massachusetts Dartmouth)


Investment and Pricing Decisions in the Rent-to-Own Industry in the Presence of Stock Outs

This study addresses the product investment decision faced by firms in the rent-to-own industry. In this setting, a customer arrives according to a random process and requests one unit of a product to rent (and eventually own should he/she choose to make all the required payments). At the time of request, if the product is available in inventory, the firm enters into a contractual agreement (by accepting the customer’s bid) and rents the merchandise. More interesting and the case considered here, if the requested item is not in inventory, the firm must decide whether to purchase the item in order to rent it out or to simply reject the bid. The bid specifies the desired maximum contract length and the payment frequency—from which the firm determines the fixed periodic payment charged. The firm makes its investment decision based on the characteristics of the bid as well as those of the product (e.g., initial and resale values, useful life and carrying costs) in essence performing a complicated cost-benefit analysis. An extension is also considered whereby instead of simply rejecting the id the firm can adjust the required payment amount. Dynamic programming techniques are used to address the problem and to solve for the firm’s optimal decision.

 Nov. 11

 Taoying Farenhorst-Yuan


"Efficient Simulation Algorithms for Optimization of Discrete Event Systems Based on Measure-Valued Differentiation"


A wide range of stochastic systems in the area of manufacturing, transportation, finance, logistics and communication can be modeled as discrete event systems (DES). In general, however, ``real world''
DESs either do not conform to some assumptions we made in order to obtain a solution, or they are just too complex to yield analytical solutions. In such cases, simulation becomes a very attractive tool for performance evaluation and optimization of DESs. Consequently, the derivatives of the performance measures have to estimated which leads to the problem of finding efficient unbiased gradient estimators. From a practical point of view, gradient estimators should, 1) be easy to implement, 2) have low variance and 3) have a low computational effort. This thesis is devoted to developing efficient gradient estimation methods for optimization of DESs and to applying these resulting algorithms to real-life problems.

Venue H10-31, time 12.00h.


Remy Spliet
Room: 11-05
Phone: 010-4081342