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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.

tight near-optimal polynomial gap unknown impossible· rows follow the assumption tree; each cell: best upper bound vs lower bound, and what forces the lower bound
Setting
Time
Budget factor
Arbitrary graphs + static graph, + undirected
1 open · 2 results
unknown \(\text{poly}(n, m)\) vs \(\text{NP-hard}\) combinatorial hardness
tight \(\min\{3,\ 1+\max_{i,j} B_i/B_j\}\) vs \(3\) combinatorial hardness
Paths + path
2 open · 1 results
polynomial gap \(O\big(\mathrm{dist}(v_s,v_t)^2\, k^{1+4\log \mathrm{dist}(v_s,v_t)}\big)\) vs \(\text{weakly NP-hard}\) combinatorial hardness
unknown — vs —
Paths, equal budgets + equal budgets
1 open · 1 results
tight \(O(k)\) vs —
tight — vs —
Arbitrary graphs, equal budgets any graph, + equal budgets
1 open · 1 results
unknown — vs \(\text{NP-hard}\) combinatorial hardness
unknown \(2\) vs —
Planar graphs, equal budgets + planar, + equal budgets
1 open · 0 results
unknown — vs \(\text{NP-hard}\) combinatorial hardness
unknown — vs —

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