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   https://doi.org/10.1016/j.tcs.2019.08.011  

   Ahmed, Abu Reyan; Saidur Rahman, Md.; Kobourov, Stephen (February 2020, Theoretical Computer Science)
2. Online Facility Assignment

   Ahmed, Reyan; Rahman, Saidur; Kobourov, Stephen (January 2018, Walcom)

   We consider the online facility assignment problem, with a set of facilities F of equal capacity l in metric space and customers arriving one by one in an online manner. We must assign customer ci to facility fj before the next customer ci+1 arrives. The cost of this assignment is the distance between ci and fj. The total number of customers is at most |F|l and each customer must be assigned to a facility. The objective is to minimize the sum of all assignment costs. We first consider the case where facilities are placed on a line so that the distance between adjacent facilities is the same and customers appear anywhere on the line. We describe a greedy algorithm with competitive ratio 4|F| and another one with competitive ratio |F|. Finally, we consider a variant in which the facilities are placed on the vertices of a graph and two algorithms in that setting. 

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3. Strategic Facility Location via Predictions

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4. Altruism in Facility Location Problems

   https://doi.org/10.1609/aaai.v38i9.28862  

   Zhou, Houyu; Chan, Hau; Li, Minming (March 2024, Proceedings of the AAAI Conference on Artificial Intelligence)

   We study the facility location problems (FLPs) with altruistic agents who act to benefit others in their affiliated groups. Our aim is to design mechanisms that elicit true locations from the agents in different overlapping groups and place a facility to serve agents to approximately optimize a given objective based on agents' costs to the facility. Existing studies of FLPs consider myopic agents who aim to minimize their own costs to the facility. We mainly consider altruistic agents with well-motivated group costs that are defined over costs incurred by all agents in their groups. Accordingly, we define Pareto strategyproofness to account for altruistic agents and their multiple group memberships with incomparable group costs. We consider mechanisms satisfying this strategyproofness under various combinations of the planner's objectives and agents' group costs. For each of these settings, we provide upper and lower bounds of approximation ratios of the mechanisms satisfying Pareto strategyproofness. 

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5. Coffea-casa: an analysis facility prototype

   https://doi.org/10.1051/epjconf/202125102061  

   Adamec, Matous; Attebury, Garhan; Bloom, Kenneth; Bockelman, Brian; Lundstedt, Carl; Shadura, Oksana; Thiltges, John (January 2021, EPJ Web of Conferences)

   Biscarat, C.; Campana, S.; Hegner, B.; Roiser, S.; Rovelli, C.I.; Stewart, G.A. (Ed.)

   Data analysis in HEP has often relied on batch systems and event loops; users are given a non-interactive interface to computing resources and consider data event-by-event. The “Coffea-casa” prototype analysis facility is an effort to provide users with alternate mechanisms to access computing resources and enable new programming paradigms. Instead of the command-line interface and asynchronous batch access, a notebook-based web interface and interactive computing is provided. Instead of writing event loops, the columnbased Coffea library is used. In this paper, we describe the architectural components of the facility, the services offered to end users, and how it integrates into a larger ecosystem for data access and authentication. 

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