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An adaptive amoeba algorithm for constrained shortest paths
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DOI：10.1016/j.eswa.2013.07.054.png)
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摘要
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The constrained shortest path problem (CSP) is one of the basic network optimization problems, which plays an important part in real applications. In this paper, an adaptive amoeba algorithm is combined with the Lagrangian relaxation algorithm to solve the CSP problem. The proposed method is divided into two steps: (1) the adaptive amoeba algorithm is modified to solve the shortest path problem (SPP) in a directed network; (2) the modified adaptive amoeba algorithm is combined with the Lagrangian relaxation method to solve the CSP problem. In addition, the evolving processes of the adaptive amoeba model have been detailed in the paper. Two examples are used to illustrate the efficiency of the proposed method. The results show that the proposed method can deal with the CSP problem effectively. (C) 2013 Elsevier Ltd. All rights reserved.
Keyword:
Constrained shortest path
Adaptive amoeba algorithm
Lagrangian relaxation
Optimization
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7.5
论文数:
3.0W
被引数:
10.2W
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