異種エージェントへのタスク割当のためのミニマックス巡回
Min-Max Tours for Task Allocation to Heterogeneous Agents
拠点から出発する異種エージェント群に、タイプ制約付きのタスクを割り当て、各エージェントの巡回コストの最大値を最小化する問題に対し、5近似（各タイプ1台なら4近似）の3段階アルゴリズムを提案した。
著者: Amritha Prasad, Han-Lim Choi, Shreyas Sundaram
分類: cs.MA, cs.RO, cs.SY, eess.SY
原文アブストラクト
We consider a scenario consisting of a set of heterogeneous mobile agents located at a depot, and a set of tasks dispersed over a geographic area. The agents are partitioned into different types. The tasks are partitioned into specialized tasks that can only be done by agents of a certain type, and generic tasks that can be done by any agent. The distances between each pair of tasks are specified, and satisfy the triangle inequality. Given this scenario, we address the problem of allocating these tasks among the available agents (subject to type compatibility constraints) while minimizing the maximum cost to tour the allocation by any agent and return to the depot. This problem is NP-hard, and we give a three phase algorithm to solve this problem that provides 5-factor approximation, regardless of the total number of agents and the number of agents of each type. We also show that in the special case where there is only one agent of each type, the algorithm has an approximation factor of 4.
