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Optimal multiunit transfer over adversarial paths with increasing intercept probabilities

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  • Christopher Garcia

Abstract

We consider a problem involving transporting a set of items over a set of hostile paths where an adversary seeks to intercept them, with the goal of maximizing the probability that all items successfully cross. Items leave a unique footprint as they cross a path, and the probability that an item is intercepted on a given path increases according to an intercept probability function as the cumulative footprint on that path increases. We provide a problem formulation and demonstrate several properties important for its solution. We then use these to develop four optimization algorithms: an exact algorithm (E), a greedy heuristic (G), a greedy heuristic with local search (LS), and a genetic algorithm (GA). These algorithms were evaluated via computational experiments on a large set of benchmark problems spanning different sizes and characteristics. LS provided the largest number of best solutions while outperforming GA in terms of solution time.

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  • Christopher Garcia, 2018. "Optimal multiunit transfer over adversarial paths with increasing intercept probabilities," IISE Transactions, Taylor & Francis Journals, vol. 50(11), pages 989-996, November.
    • Handle: RePEc:taf:uiiexx:v:50:y:2018:i:11:p:989-996
    DOI: 10.1080/24725854.2018.1488306
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