Michal Tzur’s
List of Recent Abstracts



 • Network Design in Humanitarian Supply Chains: Pre and Post Disaster Decision Making.

Reut Noham and Michal Tzur


We address location and inventory pre-positioning problems for disaster preparedness and response, under uncertainty and limited availability of resources and infrastructure. Existing models address network design and resource allocation challenges related to pre and post-disaster situations, respectively. However, they adopt a global optimization point of view, which may not be attainable, due to the actual decision making process. The latter is based mostly on practitioners' knowledge and experience, simple rules of thumb, and the local population behavior. In our work, we develop new mathematical models that represent practical considerations such as those mentioned above. For small/medium instances of the considered problem we present an efficient optimal solution method while for large instances we develop a heuristic algorithm. We test our heuristic on random, as well as on real data, and demonstrate the effectiveness of our heuristic. The results demonstrate the sensitivity of network design decisions (made at the pre-disaster phase) to post-disaster decisions. It is shown that, to the extent possible, it is critical to accurately model/predict post-disaster decisions during the pre-disaster phase.





  The Humanitarian Pickup and Distribution Problem.

Ohad Eisenhandler and Michal Tzur


Food rescue, i.e., the collection of perishable products from food suppliers who are willing to make donation, and its distribution to welfare agencies that serve individuals in need, has become increasingly widespread in recent years. This is due to economic crises that have increased the demand for nutritional aid, and the benefit to donors who can avoid in this way the costs of destroying excess production while reflecting a social-aware image. The problem we study focuses on the logistic challenges of a food bank coordinating this operation on a daily basis, using vehicles with limited capacity whose travel time cannot exceed an imposed maximal duration (defined by the driver's working hour regulations). We model this problem as a routing–allocation problem, with the aim of maintaining equitable allocations to the different agencies in each period, while delivering as much as possible in total. We discuss an appropriate objective function that promotes effectiveness and equity. We show how these two measures can be combined in a way that satisfies desired properties of the allocation, that is easy to compute and implement within a mathematical formulation, and that balances effectiveness and equity.





 Setting Inventory Levels in a Bike Sharing Network.

Sharon Datner, Tal Raviv and Michal Tzur


Bike Sharing Systems (BSS) allow customers to rent a bicycle at automatic rental stations spread around town, use them for a short period of time, and return them at any station. One of the major issues BSS operators have to deal with is the non-homogeneous asymmetric demand processes. These demand processes create an inherent imbalance, thus leading to shortage events of both bicycles when attempting to rent them, and of vacant lockers when attempting to return them. The main approach taken by operators to deal with this difficulty is repositioning bicycles so as to rebalance the inventory levels of the different stations. Most
repositioning studies assume that a target level or a range of inventory levels exist at each station. In this research we focus on determining the right target level for the repositioning activity, according to a well-defined objective. This is a challenging task, due to the nature of users' behavior that creates interactions between the inventory levels of different stations. For example, if bicycles are not available at the desired origin of a user's journey, the user may either abandon the system, possibly use other means of transportation, or she may look for available bicycles in a neighboring station. If, in another case, a locker is not available at the
destination, the user is obliged to find a station with available space in order to return the bicycle to the system. Thus, an empty/full station can create a demand spill-over to stations nearby. In addition, stations are related by origin-destination pairing. In this paper, for the first time we take this effect into consideration when setting target inventory levels and develop a robust guided local search towards that. We show that neglecting the stations' interactions leads to inferior decision making.






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Last modified: Tue Dec 15, 2015