| 摘要: |
| 针对单规格一刀切二维矩形排样问题，提出了一种启发式搜索算法，称为大小工件分治择优匹配（bigitemsmallitem divide-and-conquer best-fit，简称BSDBF）启发式算法.该算法基于组化规则，提出了大小工件分治策略和组块快速举荐算法，是对组化策略的关键补充，这对优解获得至关重要.然后，择优选择适应度高的组块进行递归排样，贪心获得各块板材的排样方案.最后，基于设计的工件拆分方法，对初始解进行后处理小规模重排，进一步提升解的质量.因为没有随机因素，其获得的优解可复现，也是BSDBF算法区别于其他算法的典型特征.大量Benchmark案例的实验结果表明，BSDBF算法求解质量优于其他算法的报道结果. |
| 关键词: 固定尺寸 装箱问题 启发式 适应度 组化 |
| DOI：10.13328/j.cnki.jos.005100 |
| 分类号: |
| 基金项目:国家科技支撑计划（2012BAF12B10）；广东省产学研项目（2012B091100025）；广东省科技计划（2015B010128007，2016A010106006）；国家自然科学基金（51675108） |
|
| Heuristic Search Algorithm for the Rectangular Fixed-Size Guillotine Bin Packing Problem |
|
WANG Lei1,2, LIU Qiang1, CHEN Xin1
|
|
1.Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System Guangdong University of Technology, Guangzhou 510006, China;2.Department of Information Engineering, Guangdong Polytechnic of Science and Trade, Guangzhou 510430, China
|
| Abstract: |
| This paper proposes a novelty heuristic search algorithm, called BSDBF (bigitem smallitem divide-and-conquer best-fit), to solve the two-dimensional rectangular fixed-size guillotine bin packing problem. First, based on group rules, this algorithm implements big item smalltime divide-and-conquer strategy and efficient group recommendation scheme which are key points to improve the group strategy. Then, the best-fit group is selected for recursive packing, and packing solution is achieved greedily for all bins. Finally, an initial solution is obtained, and a post processing algorithm is used to improve the quality of the solution based on item splitting method. That the solution can be obtained again is the critical characteristic of BSDBF algorithm which is different from others algorithms, because there is not any random factor in BSDBF algorithm. The computational results of many Benchmark problems have shown that BSDBF algorithm outperforms others reported algorithms. |
| Key words: fixed-size bin packing heuristic fitness group |
