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Foraging-directed adaptive linear programming (FALP): a hybrid algorithm for discrete/continuous design problems

机译:觅食指导的自适应线性规划(FALP):离散/连续设计问题的混合算法

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摘要

In this paper, a hybrid, two-stage algorithm, namely, Foraging-directed Adaptive Linear Programming is introduced. The second stage, Adaptive Linear Programming, has been presented in detail elsewhere. Hence, in this paper, the focus is on the first stage which is based on the notion of animals foraging for food in the wild. Two problems are included. In the first, significantly better solutions than previous studies are found and global optimality can be proven. In the second, more complex problem, finding a global optimum is difficult, but various solutions that may not be optimal but are as good or better than previous reports can be found. Therefore, depending upon the complexity of a given problem, the algorithm presented is able to find optimal solutions or identify satisficing solutions or regions where good solutions are located.
机译:本文介绍了一种混合两阶段算法,即觅食指导的自适应线性规划。第二阶段,自适应线性规划,已在其他地方进行了详细介绍。因此,在本文中,重点放在第一阶段,该阶段基于动物在野外觅食的概念。包括两个问题。首先,发现比以前的研究明显更好的解决方案,并且可以证明全局最优性。在第二个更复杂的问题中,很难找到一个全局最优解,但是可以找到各种可能不是最优解但与以前的报告一样好或更好的解决方案。因此,根据给定问题的复杂性,提出的算法能够找到最佳解决方案或识别令人满意的解决方案或好的解决方案所在的区域。

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