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  • Smith, J. Cole  (4)
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  • 1
    Online Resource
    Online Resource
    Informa UK Limited ; 2017
    In:  IISE Transactions Vol. 49, No. 12 ( 2017-12-02), p. 1112-1128
    In: IISE Transactions, Informa UK Limited, Vol. 49, No. 12 ( 2017-12-02), p. 1112-1128
    Type of Medium: Online Resource
    ISSN: 2472-5854 , 2472-5862
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2017
    detail.hit.zdb_id: 2880610-4
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  • 2
    In: Journal of Applied Ecology, Wiley, Vol. 52, No. 6 ( 2015-12), p. 1588-1597
    Abstract: This application of interdiction models prescribed a combination of patches for protection that results in the least possible decrease in life expectancy. Our analyses of the snail kite and roseate tern networks suggest that managing to protect these prescribed patches by the network fortification ‐interdiction models (i.e. protecting against the worst‐case disturbance scenario) is more beneficial than managing patches that minimize dispersal distance or maximize the number of individuals under protection if the conservation goal is to ensure the long‐term persistence of a species.
    Type of Medium: Online Resource
    ISSN: 0021-8901 , 1365-2664
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2015
    detail.hit.zdb_id: 2020408-5
    detail.hit.zdb_id: 410405-5
    SSG: 12
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2017
    In:  Naval Research Logistics (NRL) Vol. 64, No. 5 ( 2017-08), p. 373-387
    In: Naval Research Logistics (NRL), Wiley, Vol. 64, No. 5 ( 2017-08), p. 373-387
    Abstract: We study a multi‐stage dynamic assignment interdiction (DAI) game in which two agents, a user and an attacker, compete in the underlying bipartite assignment graph. The user wishes to assign a set of tasks at the minimum cost, and the attacker seeks to interdict a subset of arcs to maximize the user's objective. The user assigns exactly one task per stage, and the assignment costs and interdiction impacts vary across stages. Before any stage commences in the game, the attacker can interdict arcs subject to a cardinality constraint. An interdicted arc can still be used by the user, but at an increased assignment cost. The goal is to find an optimal sequence of assignments, coupled with the attacker's optimal interdiction strategy. We prove that this problem is strongly NP‐hard, even when the attacker can interdict only one arc. We propose an exact exponential‐state dynamic‐programming algorithm for this problem as well as lower and upper bounds on the optimal objective function value. Our bounds are based on classical interdiction and robust optimization models, and on variations of the DAI game. We examine the efficiency of our algorithms and the quality of our bounds on a set of randomly generated instances. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 373–387, 2017
    Type of Medium: Online Resource
    ISSN: 0894-069X , 1520-6750
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 392494-4
    detail.hit.zdb_id: 207110-1
    detail.hit.zdb_id: 1465691-7
    SSG: 8
    SSG: 3,2
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  • 4
    Online Resource
    Online Resource
    Wiley ; 2016
    In:  Networks Vol. 68, No. 4 ( 2016-12), p. 315-330
    In: Networks, Wiley, Vol. 68, No. 4 ( 2016-12), p. 315-330
    Abstract: We study a dynamic network game between an attacker and a user. The user wishes to find a shortest path between a pair of nodes in a directed network, and the attacker seeks to interdict a subset of arcs to maximize the user's shortest‐path cost. In contrast to most previous studies, the attacker can interdict arcs any time the user reaches a node in the network, and the user can respond by dynamically altering its chosen path. We assume that the attacker can interdict a limited number of arcs, and that an interdicted arc can still be traversed by the user at an increased cost. The challenge is therefore to find an optimal path (possibly repeating arcs in the network), coupled with the attacker's optimal interdiction strategy (i.e., which arcs to interdict and when to interdict them). We propose an exact exponential‐state dynamic‐programming algorithm for this problem, which can be reduced to a polynomial‐time algorithm in the case of acyclic networks. We also develop lower and upper bounds on the optimal objective function value based on classical interdiction and robust optimization models, or based on an exact solution to variations of this problem. We examine the efficiency of our algorithms and the quality of our bounds on a set of randomly generated instances. © 2016 Wiley Periodicals, Inc. NETWORKS, Vol. 68(4), 315–330 2016
    Type of Medium: Online Resource
    ISSN: 0028-3045 , 1097-0037
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 1481067-0
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