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June
Six internal OR seminars
March 26
Speaker: Son Tran
Title: Anticipatory order picking
Description: Order picking describes the process of retrieving a set of products from a warehouse in response to newly incoming customer orders. To mitigate demand uncertainty and improve the efficiency of the picking operations, we explore the idea of anticipatory order picking (AOP). In AOP, expected (but uncertain) customer orders are considered when planning and executing order picking activities. In contrast to the confirmed orders, these expected orders - if picked - are stored in a buffer zone close to the packing and/or labeling station from which they can be retrieved with very limited travel time. Extensive simulation experiments revealed the following advantages: better workload balancing, reduction in warehouse traffic, and earlier completion time. In this talk, I also want to discuss our idea of using machine learning to further the study of AOP.
December 11
Speaker: Tim Oosterwijk
Title: Flows over Time with Costs and Deadlines
Description: In this talk, I will introduce a new network flow over time model in which particles minimize their costs subject to the constraint that they arrive at the sink before a specified deadline. I will show you our results about the structure of equilibria and an infinite Price of Anarchy, and we can discuss future research directions. This is joint work with Marc Schröder and Daniel Schmand.
October 30
Speaker: Farzaneh Rajabighamchi
Title: Order picker routing problem
Description: Farzaneh will try to find an exact mathematical model in addition to graph reduction algorithm to make the network smaller. She will try to see if this model is faster and more efficient than the heuristics or not.
October 9
Speaker: Marc Schröder
Title: Scheduling with Machine-Dependent Priority Lists
Description: We consider a scheduling problem in which each machine uses an individual priority list to decide on the order according to which the jobs on the machine are processed. The goal is to find a schedule that minimizes the sum of completion times. The problem is polynomially solvable if we have a constant number of machines and all machines use the same priority list. The problem is NP-hard if the number of machines is part of the input and machines are allowed to have different priority lists. This is joint work with Vipin Ravindran Vijayalakshmi and Tami Tamir.
September 18
Speaker: Moritz Buchem
Title: Additive approximation schemes for load balancing problems (and beyond?)
Description: We give a short overview of our results for additive approximation schemes on parallel machines (joint work with Lars Rohwedder (EPFL), Tjark and Andreas Wiese (Universidad de Chile)) and discuss open questions and possible other directions and problems in which additive approximation schemes could be of interest.