Finding a risk-constrained shortest path for an unmanned combat vehicle

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We consider a problem of finding a reconnaissance route of an unmanned combat vehicle (UCV) in a terrain, which is modeled as a grid. It is assumed that the traverse time to pass through each cell in the grid and risk level associated with each cell are given and that the cells where the reconnaissance points to be visited by the UCV are located and the visiting sequence of such cells are given in advance as in real situation of military operation. We focus on the problem with the objective of minimizing the total travel time of the UCV for a given limit on the sum of risk level values associated with the cells on the path of the UCV. We develop an optimal solution algorithm based on a dynamic programming algorithm for multiple-choice knapsack problems. We also present a heuristic algorithm, which can be used for large-size problems. For evaluation of the performance of the proposed algorithms, computational experiments are performed on a number of problem instances, and results show that the proposed algorithms give optimal or good solutions within an acceptable time for real military operations.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2015-02
Language
English
Article Type
Article
Keywords

TRAVELING-SALESMAN PROBLEM; HEAD PLACEMENT MACHINES; CHOICE KNAPSACK-PROBLEM; GENETIC ALGORITHM; SCHEDULING PROBLEM; SIDE CONSTRAINTS; APPROXIMATION; GENERATION; OPERATIONS; BRANCH

Citation

COMPUTERS INDUSTRIAL ENGINEERING, v.80, pp.245 - 253

ISSN
0360-8352
DOI
10.1016/j.cie.2014.12.016
URI
http://hdl.handle.net/10203/195800
Appears in Collection
IE-Journal Papers(저널논문)
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