Comparisons and Applications of Local and Global Search

IRI-9503366惠特利湖达雷尔科罗拉多州立大学$90，000 - 12个月。 局部搜索与全局搜索的比较及应用 这是第一年发现的三年连续赠款。 科学家和工程师寻求实用的方法来解决困难的组合优化问题，越来越多地转向局部搜索和遗传算法。 此外，在过去的五年里，研究人员提出了这些技术的新变体，特别是遗传算法。 最近的遗传算法的工作强烈建议最好的算法交织局部搜索和遗传搜索技术。 这项研究有四个主要目标：1）产生一套局部搜索方法和随机爬山算法来测试优化问题的难度，2）产生一套新的抗局部搜索和随机爬山的复杂问题测试集，3）产生新的杂交遗传算法，可以用于产生最先进的结果，用于计算机视觉和物理学的应用，4）对主要的遗传算法搜索范例进行比较研究，包括利用局部搜索的混合算法。 在追求这第四个目标，这将是必要的，以比较不同的遗传算法，局部搜索算法，并在控制测试套件的问题，以及实际重要性的大问题的混合动力。

IRI-9503366 Whitley, L. Darrell Colorado State University $90,000 - 12 mos. Comparisons and Applications of Local and Global Search This is first year finding for a three year continuing grant. Scientists and engineers seeking practical ways to solve difficult combinatorial optimization problems are increasingly turning to local search and genetic algorithms. In addition, the past five years has seen a dramatic increase in researchers proposing new variants on these techniques, especially genetic algorithms. Recent work on genetic algorithms has strongly suggested the best algorithms interweave local search and genetic search techniques. This research has four main objectives: 1) produce a suite of local search methods and stochastic hill-climbing algorithms to test the difficulty of optimization problems, 2) produce a new test suite of complex problems which are resistant to local search and stochastic hill-climbing, 3) produce new hybridized genetic algorithms that can be sued to produce state-of-the-art results for applications in computer vision and geophysics, 4) conduct comparative studies of the major genetic algorithm search paradigms, including hybrids which utilize local search. In pursuit of this fourth objective, it will be necessary to compare different genetic algorithms, local search algorithms, and hybrids on both the controlled test suite of problems as well as large problems of practical importance.