Reallocating Multiple Facilities on the Line

Authors: Dimitris Fotakis, Loukas Kavouras, Panagiotis Kostopanagiotis, Philip Lazos, Stratis Skoulakis, Nikos Zarifis

IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Using an LP-based approach, we present a polynomial time algorithm that computes the optimal solution for any number of facilities. We also consider online K-facility reallocation, where the algorithm becomes aware of agent locations in a stage-by-stage fashion. By exploiting an interesting connection to the classical K-server problem, we present a constant-competitive algorithm for K = 2 facilities.
Researcher Affiliation Academia Dimitris Fotakis1 , Loukas Kavouras1 , Panagiotis Kostopanagiotis1 , Philip Lazos2 , Stratis Skoulakis1 and Nikos Zarifis1 1National Technical University of Athens 2Sapienza University of Rome
Pseudocode Yes Algorithm 1: Algorithm for the offline case ... Algorithm 2: Selecting xt 1 and xt 2
Open Source Code No The paper states: 'Due to space limitations, most proofs are omitted and can be found in https://128.84.21.199/pdf/1905.12379.pdf.' This link points to a PDF, not source code. There are no other explicit statements about code availability for the described methodology.
Open Datasets No The paper is theoretical and focuses on algorithm design and proofs of optimality and competitiveness. It does not describe experiments or use specific datasets that would be trained on. Therefore, there is no mention of publicly available or open datasets.
Dataset Splits No The paper is theoretical and does not describe empirical experiments or dataset evaluations. Therefore, there are no mentions of training, validation, or test dataset splits.
Hardware Specification No The paper is theoretical and focuses on algorithm design and analysis. It does not describe any computational experiments or mention any hardware specifications used.
Software Dependencies No The paper is theoretical and describes algorithms (e.g., LP-based approach). While it refers to Integer Linear Programs, it does not specify any particular software, libraries, or solvers with version numbers that would be used to implement or run them.
Experiment Setup No The paper is theoretical and focuses on algorithm design and analysis. It does not describe any experimental setup, hyperparameters, or training configurations.