Delivery by energy-constrained agents
Agents with energy budgets, placed in a weighted graph, must carry a message from a source node to a target node, handing it over when they meet: when can a planner find a schedule quickly, and by how much must the budgets grow?
Problem statement and measuresexpand
\(k\) agents start at nodes of a connected undirected graph \(G\) with \(n\) nodes and \(m\) edges; every edge \(e\) has a positive weight \(\mathrm{wt}(e)\), its length. Agent \(i\) has a budget \(B_i\): it can travel a total distance of at most \(B_i\), also along parts of edges. A message lies at a source node \(v_s\) and must reach a target node \(v_t\). An agent can pick the message up where it is, carry it, and drop it anywhere (at a node or inside an edge), where another agent can pick it up; agents need not return to their start nodes. A planner that knows \(G\), the start nodes and the budgets computes a schedule: which agents move, and where each one picks up and drops the message. The task is to decide whether a schedule exists and to find one. Time is the running time of the planner. The budget factor \(\gamma\) is that of a planner that runs in polynomial time and either correctly reports that no schedule exists or finds one in which every agent may travel \(\gamma B_i\) (resource augmentation); with equal budgets \(B_i = B\), it is the ratio between the budget the planner uses and the smallest budget that admits a schedule.
Measures: Time, running time of the planner; Budget factor, factor by which a polynomial-time planner enlarges the budgets (resource augmentation), or its approximation ratio for the smallest equal budget.
Planar graphs, equal budgets
verifiedDelivery stays strongly NP-hard on planar graphs, even when all budgets are equal.
Assumed (added on the last edge are outlined)
Not assumed
Formal definitions of this setting
- Graph dynamics: static graph
- \(G_t=G\) for all \(t\): the edge set never changes.
- Edge direction: undirected
- \(G=(V,E)\) with \(E\subseteq\binom V2\); every edge can be traversed in both directions.
- Graph class: planar
- \(G\) is planar.
- Budgets: equal budgets
- All agents have the same budget \(B\).
What is known
- strongly NP-hard, by a reduction from planar 3SAT (Theorem 5)
- equal budgets: an edge of length \(B - B_i\) is added at each agent's start node, and the agent moved to its end
Results, in order of publication
No result recorded yet.
Open questions
Is there an inapproximability bound for the smallest equal budget, already on planar graphs? No lower bound above 1 is known for any graph class Chalopin et al. 2021.
Notes
The same reduction shows returning delivery strongly NP-hard on planar graphs Bärtschi et al. 2020. Checked against the full text (arXiv v1).
What carries over from neighbouring settings
Read off the order of assumptions, not checked case by case: results may carry extra assumptions (shown on their pages), and asynchronous time is measured in epochs.
Algorithms from weaker settings work here
Lower bounds from stronger settings hold here
Know a better result for this setting, or found a mistake? Suggest a result · Report an error. Accepted contributions are acknowledged.