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Embedding branch and bound within evolutionary algorithms

机译:将分支和边界嵌入进化算法中

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摘要

A framework for hybridizing evolutionary algorithms with the branch-and-bound algorithm (B&B) is presented in this paper. This framework is based on using B&B as an operator embedded in the evolutionary algorithm. The resulting hybrid operator will intelligently explore the dynastic potential (possible children) of the solutions being recombined, providing the best combination of formae (generalized schemata) that can be constructed without introducing implicit mutation. As a basis for studying this operator, the general functioning of transmitting recombination is considered. Two important concepts are introduced, compatibility sets, and granularity of the representation. These concepts are studied in the context of different kinds of representation: orthogonal, non-orthogonal separable, and non-separable. The results of an extensive experimental evaluation are reported. It is shown that this model can be useful when problem knowledge is available in the form of an optimistic evaluation function. Scalability issues are also considered. A control mechanism is proposed to alleviate the increasing computational cost of the algorithm for highly multidimensional problems. [References: 36]
机译:本文提出了一种将进化算法与分支定界算法(B&B)混合的框架。该框架基于使用B&B作为嵌入在进化算法中的运算符。由此产生的混合算子将智能地探索被重组解决方案的王朝潜力(可能的子代),从而提供无需引入隐式突变即可构建的最佳形式(广义图解)组合。作为研究该算子的基础,考虑了发送重组的一般功能。引入了两个重要的概念:兼容性集和表示的粒度。这些概念是在各种表示形式的上下文中研究的:正交,非正交可分离和不可分离。报告了广泛的实验评估结果。结果表明,当问题知识以乐观评估函数的形式可用时,该模型将非常有用。还考虑了可伸缩性问题。提出了一种控制机制来减轻针对高度多维问题的算法的计算成本增加。 [参考:36]

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