Adopting gene expression programming to generate extension strategies for incompatible problem
Adopting gene expression programming to generate extension strategies for incompatible problem
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DOI：
10.1007/s00521-016-2211-1
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发表时间：
2017-09
影响因子：
6
通讯作者：
Long Tang;Chunyan Yang;Weihua Li
中科院分区：
文献类型：
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作者：
Long Tang;Chunyan Yang;Weihua Li
探索不相容问题的解决策略是一项具有挑战性的任务。尽管可拓策略生成方法(ESGM)可以通过扩展推理和可拓变换来解决不相容问题，但求解过程中往往会遇到计算代价的组合爆炸。为了克服这一缺陷，提出了一种基于基因表达式编程(GEP)的可拓变换方法。该方法能够启发式、迭代地建立可拓变换的优势运算，有效地避免了组合爆炸。为了使GEP能够适应这种应用需求，对染色体结构、译码方式、个体选择和收敛准则进行了重新研究。最后，将该方法应用于自助游路线设计问题。数值结果表明，该方法能够有效地提供可拓策略，对于求解更复杂的不相容问题具有巨大的潜力。
Exploring solving strategies for incompatible problem is a challenging task. Although extension strategy generating method (ESGM) can address incompatible problem by expanding reasoning and extension transformations, the solving process often suffers a combination explosion of computational cost. In order to overcome this shortcoming, a new approach to performing extension transformations based on gene expression programming (GEP) is proposed. The method is able to establish superior operations of extension transformations heuristically and iteratively, which avoids the combination explosion effectively. In order to make GEP adapt to such applying requirement, chromosome architecture, decoding mode, individual selection and convergence criteria are restudied. The proposed method is illustrated with the application of ESGM to a self-guided touring route design problem. Numerical results verify that the proposed method helps provide extension strategies efficiently and has a huge potential for more complex incompatible problem solving.