searchalgorithms for solving CSP (Constraint Satisfaction Problems) usually fall into one of two main families: local searchalgorithms and systematic algorithms. Both families have their advantages. Designing hybrid...
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searchalgorithms for solving CSP (Constraint Satisfaction Problems) usually fall into one of two main families: local searchalgorithms and systematic algorithms. Both families have their advantages. Designing hybrid approaches seems promising since those advantages may be combined into a single approach. In this paper, we present a new hybrid technique. It performs a local search over partial assignments instead of complete assignments, and uses filtering techniques and conflict-based techniques to efficiently guide the search. This new technique benefits from both classical approaches: a priori pruning of the search space from filtering-based search and possible repair of early mistakes from local search. We focus on a specific version of this technique: tabu decision-repair. Experiments done on open-shop scheduling problems show that our approach competes well with the best highly specialized algorithms. (C) 2002 Elsevier Science B.V. All rights reserved.
A decision method using multiple threshold values for PN code acquisition in DS-CDMA systems is described. This technique is applied to a conventional hybrid search algorithm and analysed in terms of the probability o...
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A decision method using multiple threshold values for PN code acquisition in DS-CDMA systems is described. This technique is applied to a conventional hybrid search algorithm and analysed in terms of the probability of detection and false alarm. Simulation results show that the proposed scheme outperforms the conventional scheme in terms of detection probability because multiple threshold values mitigate any possible decline in performance caused bq the use of a single threshold.
Visual reconstruction refers to extracting stable descriptions from visual data ([1];A. Blake and A. Zisserman, Visual Reconstruction, MIT Press, Cambridge, MA, 1987). Visual reconstruction problems are commonly formu...
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Visual reconstruction refers to extracting stable descriptions from visual data ([1];A. Blake and A. Zisserman, Visual Reconstruction, MIT Press, Cambridge, MA, 1987). Visual reconstruction problems are commonly formulated in an optimization framework and normally require the optimization of nonconvex functions especially when discontinuity preserving image/shape recovery is the goal. Example problems include, image restoration, surface reconstruction, shape from shading etc. Most existing deterministic methods fail to reach the global optimum and lack the generality to incorporate reasonably complex interactions between boolean valued line process variables used for representing the presence (absence) of discontinuities. Stochastic methods for solving such problems e.g. the simulated annealing algorithm or variants thereof do achieve a global optimum but are plagued by slow convergence rates. In this paper, we present a new hybrid search algorithm as an efficient solution for achieving the global optimum of the nonconvex function derived from a Markov random field formulation which allows for incorporation of complex interactions between the line process variables to better constraint the line processes. In the hybridsearch, for the stochastic part, we develop an informed genetic algorithm (GA) while employing an incomplete Cholesky preconditioned conjugate gradient algorithm ([23];S.H. Lai and B.C. Vemuri, Robust and efficient algorithms for optical flow computation, in: Proceedings of the International Symposium on Computer Vision, Coral Gables, FL, 1995, pp. 455-460) for the deterministic part. Our informed GA consists of a reproduction operator and an informed mutation operator. The informed mutation operator exploits specific domain knowledge in the search and is accomplished by the Gibbs sampler. Our hybrid search algorithm is highly parallelizable and leads to a globally optimal solution. The performance of our algorithm is demonstrated via experimental res
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