J. Gu and X. Huang, "Efficient Local Search With Search Space Smoothing: A Case Study of the Traveling Salesman Problem (TSP)," IEEE Trans. System Man & Cybernetics, 24(5):728--735, 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....[34] although without the use of refinement at each level. However the idea is only presented as a possible solution technique and no results are given. A second idea perhaps more closely related to the principles behind multilevel refinement is the search space smoothing scheme of Gu Huang, [12]. This uses recursive smoothing (analogous to recursive coarsening) to produce versions of the original problem which are simpler to solve. Thus in the example application Gu Huang apply their technique to the TSP by forcing the inter city edges to become increasingly uniform in length at each ....

J. Gu and X. Huang. Efficient Local Search With Search Space Smoothing: A Case Study of the Traveling Salesman Problem (TSP). IEEE Trans. Syst. Man & Cybernetics, 24(5):728--735, 1994.

....value. This problem has already attracted some attention in the integer programming community (see [6] 7] 10] 12] and [11] Here we present an integer programming formulation that uses Steiner cut inequalities We note that there are several good heuristic methods based on local search [16, 13, 15] that can also be used for approximate solutions to costly combinatorial problems. However, we are interested in the exact solutions. For any proper subset S of V , we denote the collection of edges with one endpoint in S and the other in V n S by ffi(S) Note that ffi(S) ffi(V n S) We choose ....

J. Gu and X. Huang. Efficient local search with search space smoothing: A case study of the traveling salesman problem (tsp). IEEE Trans. on System, Man and Cybernetics, 24-5:728--735.

....and the MAD heuristic are two improved heuristic methods presented in [4] Extensive experimental results showed that, among the three heuristics, the IMP heuristic produces the best solution. Recently the multispace search approach has been developed for solving general optimization problems [7, 9, 8]. In this paper, we apply the multispace search to solve the quorumcast routing problem. The technique is capable of smoothing the rugged terrain surface of the search space. It interplays structural operations on the objective function in conjunction with the local search algorithms. Structural ....

....value space, but also scrambles across the variable space and other active spaces. It has been proven to be efficient to overcome the pathological phenomena in combinatorial optimization problems. In this paper, the proposed multispace search algorithm will scramble in the objective function space [9]. For a given network, the costs of different links may be different, which makes the search space rugged. We use a smoothing factor, ff, to characterize the degree of a smoothing operation on the objective function and the smoothness of the resulting search space. For the quorumcast routing ....

J. Gu and X. Huang. Efficient local search with search space smoothing. IEEE Trans. on Systems, Man, and Cybernetics, 24(5):728--735, May 1994.

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J. Gu and X. Huang, "Efficient Local Search With Search Space Smoothing: A Case Study of the Traveling Salesman Problem (TSP)," IEEE Trans. System Man & Cybernetics, 24(5):728--735, 1994.

No context found.

J. Gu and X. Huang. Efficient Local Search With Search Space Smoothing: A Case Study of the Traveling Salesman Problem (TSP). IEEE Trans. Syst. Man & Cybernetics, 24(5):728--735, 1994.

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