论文标题
应用基因表达编程解决一维bin包装问题
Applying Gene Expression Programming for Solving One-Dimensional Bin-Packing Problems
论文作者
论文摘要
这项工作旨在研究和探索基因表达编程（GEP）在解决在线bin包装问题中的使用。主要思想是展示GEP如何自动找到可接受的启发式规则来有效，经济地解决该问题。在这项工作的过程中，考虑了一个维垃圾箱包装问题，并限制了填充给定材料的垃圾箱的数量。实验数据包括从Falkenauer（1996）获取的基准测试数据的实例，以解决一维bin包装问题。结果表明，GEP可以用作一个非常强大且灵活的工具，用于查找适合该问题的有趣的紧凑规则。还研究了功能的影响，以显示它们在规则中出现时如何影响和影响利率的成功。与使用遗传编程进行的先前工作相比，人口规模较小，人口规模较小，几代人的产量较小。
This work aims to study and explore the use of Gene Expression Programming (GEP) in solving the on-line Bin-Packing problem. The main idea is to show how GEP can automatically find acceptable heuristic rules to solve the problem efficiently and economically. One dimensional Bin-Packing problem is considered in the course of this work with the constraint of minimizing the number of bins filled with the given pieces. Experimental Data includes instances of benchmark test data taken from Falkenauer (1996) for One-dimensional Bin-Packing Problems. Results show that GEP can be used as a very powerful and flexible tool for finding interesting compact rules suited for the problem. The impact of functions is also investigated to show how they can affect and influence the success of rates when they appear in rules. High success rates are gained with smaller population size and fewer generations compared to previous work performed using Genetic Programming.
