This paper proposes a model for a robust shortest path problem with random edge costs. The proposed model is formulated as a bicriteria optimization problem to minimize the total cost of the path from a start node to an end node as well as to maximize the range of the confidence interval satisfying the condition that the total cost of any path in the region is less than a target value in terms of robustness. It is not always the case that a solution that simultaneously optimizes all of the objectives exists when the objectives conflict with each other. In this paper, fuzzy goals for both objectives and the aggregation function are introduced in a solution approach that considers the decision maker's preference and the subjectivity of her or his judgment in multicriteria decision making. The fuzzy bicriteria problem is transformed into a constrained shortest path problem. Furthermore, an exact algorithm based on Dijkstra's algorithm and a heuristic algorithm based on the Lagrange relaxation-based algorithm are developed for the constrained shortest path problem. (C) 2012 Elsevier Inc. All rights reserved.
机构:
Istituto dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), 6928 Lugano-MannoIstituto dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), 6928 Lugano-Manno
Montemanni R.
Gambardella L.M.
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Istituto dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), 6928 Lugano-MannoIstituto dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), 6928 Lugano-Manno
机构:
Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar UniversityDepartment of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University
Sengupta A.
Pal T.K.
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Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar UniversityDepartment of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University