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Abstract
Let G = (V, E) be a directed graph with rewards r e for e ∈ E. We show that if there exists an s, t-walk in G of length k > |V|2 then there exists a maximum reward s, t-walk of length k with at least k − |V|2 arcs from a cycle with maximal mean reward. If A is the reward-incidence matrix of G, then the maximum rewards of s, t-walks of length k can be determined by computing the k-fold matrix product A ⊗ k , where the operations “plus” and “times” are replaced by “max” and “plus” (denoted by ⊕ and ⊗). Max-algebra dynamic systems y(k) = y(k − 1) ⊗ A have been used to model certain transportation and automated manufacturing systems, and can be interpreted as deterministic dynamic programming recursions. If G is strongly connected, then y(k + d A ) = y(k) + d A λ*1 for all k ≥ K A , where λ* is the maximum cycle mean in G, and K A and d A are the max-algebra transient and period (cyclicity) of A. For given y(0), the transient τ and period γ of the system may satisfy τ < K A and γ < d A . We derive a tight bound on K A and give polynomial algorithms for computing K A , τ and γ, and for solving deterministic dynamic programming problems. We also give analogous results for walks of maximum β-discounted reward.
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Cite it as
@article{hartmann1999transience,
title = {Transience Bounds for Long Walks},
author = {Mark E. Hartmann and Cristina Arguelles},
year = {1999},
journal = {Mathematics of Operations Research},
publisher = {Institute for Operations Research and the Management Sciences},
volume = {24},
number = {2},
pages = {414--439},
doi = {10.1287/moor.24.2.414},
}