Solving Dynamic Traveling Salesman Problem Using Dynamic Gaussian Process Regression
نویسندگان
چکیده
منابع مشابه
Corrigendum to "Solving Dynamic Traveling Salesman Problem Using Dynamic Gaussian Process Regression"
This paper solves the dynamic traveling salesman problem (DTSP) using dynamic Gaussian Process Regression (DGPR) method. The problem of varying correlation tour is alleviated by the nonstationary covariance function interleaved with DGPR to generate a predictive distribution for DTSP tour. This approach is conjoined with Nearest Neighbor (NN) method and the iterated local search to track dynami...
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Problem statement: Traveling Salesman Problem (TSP) is a famous NP hard problem. Many approaches have been proposed up to date for solving TSP. We consider a TSP tour as a dependent variable and its corresponding distance as an independent variable. If a predictive function can be formulated from arbitrary sample tours, the optimal tour may be predicted from this function. Approach: In this stu...
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In this paper, we introduce a new approach for solving the traveling salesman problems (TSP) and provide a solution algorithm for a variant of this problem. The concept of the proposed method is based on the Hungarian algorithm, which has been used to solve an assignment problem for reaching an optimal solution. We introduced a new fittest criterion for crossing over such problems, and illu...
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The Traveling Salesman Problem (TSP) is one of the classic NP hard optimization problems. The Dynamic TSP (DTSP) is arguably even more difficult than general static TSP. Moreover the DTSP is widely applicable to real-world applications, arguably even more than its static equivalent. However its investigation is only in the preliminary stages. There are many open questions to be investigated. Th...
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ژورنال
عنوان ژورنال: Journal of Applied Mathematics
سال: 2014
ISSN: 1110-757X,1687-0042
DOI: 10.1155/2014/818529