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- W4299805441 abstract "In this paper, we consider a network of agents that has to self-assign a set of tasks while respecting resource constraints. One possible formulation is the Generalized Assignment Problem, where the goal is to find a maximum payoff while satisfying capability constraints. We propose a purely distributed branch-and-price algorithm to solve this problem in a cooperative fashion. Inspired by classical (centralized) branch-and-price schemes, in the proposed algorithm each agent locally solves small linear programs, generates columns by solving simple knapsack problems, and communicates to its neighbors a fixed number of basic columns. We prove finite-time convergence of the algorithm to an optimal solution of the problem. Then, we apply the proposed scheme to a generalized assignment scenario in which a team of robots has to serve a set of tasks. We implement the proposed algorithm in a ROS testbed and provide experiments for a team of heterogeneous robots solving the assignment problem." @default.
- W4299805441 created "2022-10-03" @default.
- W4299805441 creator A5061968220 @default.
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- W4299805441 date "2020-04-24" @default.
- W4299805441 modified "2023-09-26" @default.
- W4299805441 title "Generalized Assignment for Multi-Robot Systems via Distributed Branch-And-Price" @default.
- W4299805441 doi "https://doi.org/10.48550/arxiv.2004.11857" @default.
- W4299805441 hasPublicationYear "2020" @default.
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