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首页> 外文会议>First International Conference on Manufacturing Research (ICMR2003) Sep 9-11, 2003 University of Strathclyde, UK >Integrating genetic programming into job shop scheduling problem
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Integrating genetic programming into job shop scheduling problem

机译：将遗传编程整合到车间调度问题中

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摘要

Job shop Scheduling problem (JSSP) is one of the hardest combinatorial problems, which is evident from the abundance of existing literature, presenting wide range of algorithms to tackle the problem. Some of the algorithms are based on artificial intelligence concepts or they are derived from observing natural phenomena, while some others use various other tools ranging from mathematical programming to graph theory. The flavour and content of any algorithm, in general, depends on algorithm developer's background, intuition and initiative. In short the algorithm may reflect the developer's human weakness and hence subject to errors and ineffectiveness. To overcome this, we propose a multi-levels Genetic Programming (GP) system combining the strength from evolution of the algorithm structures, neighbourhood schemes and properties associated to the entities of a JSSP.
机译：作业车间调度问题（JSSP）是最困难的组合问题之一，这从大量现有文献中可以明显看出，提出了多种解决问题的算法。其中一些算法基于人工智能概念，或者源自观察自然现象，而另一些算法则使用从数学编程到图论的各种其他工具。通常，任何算法的风格和内容都取决于算法开发人员的背景，直觉和主动性。简而言之，该算法可能反映了开发人员的人为弱点，因此容易出错和无效。为了克服这个问题，我们提出了一个多层次的遗传规划（GP）系统，该系统结合了算法结构，邻域方案和与JSSP实体相关联的属性的演变而来的优势。

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