Scatter Search and Local NLP Solvers: A Multistart Framework for Global Optimization
نویسندگان
چکیده
منابع مشابه
Scatter Search and Local NLP Solvers: A Multistart Framework for Global Optimization
T algorithm described here, called OptQuest/NLP or OQNLP, is a heuristic designed to find global optima for pure and mixed integer nonlinear problems with many constraints and variables, where all problem functions are differentiable with respect to the continuous variables. It uses OptQuest, a commercial implementation of scatter search developed by OptTek Systems, Inc., to provide starting po...
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We introduce a multistart local search-based method with a taboo step for solving continuous global optimization problems with bound constraints. Since this algorithm has a characteristic taboo step[5, 1995] by removing candidate points that converge to the current local optimum in each iteration, the step enables us to avoid repeated convergence to one of an already known optima in a local sea...
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The cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. To enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. Normally, the parametersof the cuckoo search are kept constant. This may lead todecreasing the efficiency of the algorithm. To cop...
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The problem of finding a global optimum of an unconstrained multimodal function has been the subject of intensive study in recent years, giving rise to valuable advances in solution methods. We examine this problem within the framework of adaptive memory programming (AMP), focusing particularly on AMP strategies that derive from an integration of Scatter Search and Tabu Search. Computational co...
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ژورنال
عنوان ژورنال: INFORMS Journal on Computing
سال: 2007
ISSN: 1091-9856,1526-5528
DOI: 10.1287/ijoc.1060.0175