受启动空间约束的装箱问题  

On a Constrained Bin Packing Problem with Start-Up Space

作　　者：顾晓东[1,2] 许胤龙[1,2] 陈国良[1,2] 黄刘生[1,2] 

机构地区：[1]国家高性能计算中心(合肥),安徽合肥230027 [2]中国科学技术大学计算机科学与技术系,安徽合肥230027

出　　处：《软件学报》2002年第3期390-397,共8页Journal of Software

基　　金：国家重点基础研究发展规划973资助项目(G1998030403)~~

摘　　要：提出了一种带有启动空间的约束装箱问题(start-up bin packing problem,简称SBPP),即不同类型的物品放入同一箱子中需要一个启动空间.该问题在工作分配、任务调度和日常生活中的包装等问题中有着广泛的应用背景.给出了一个求解SBPP的线性脱线算法C-NF,其最坏情况渐近性能比为2,与启动空间的大小无关.对该算法的平均性能进行了实验分析.另外,还分析了SBPP的在线特性,指出大量的经典在线装箱算法应用于SBPP都不存在确定的最坏情况渐近性能比,也给出了一种具有确定的最坏情况渐近性能比的在线算法.A constrained bin packing problem with start-up space (SBPP) is proposed in this paper, in which an additional start-up space is needed if different items are put into a same bin. The problem has many applications such as job allocation, multiprocessor scheduling and real-world packing. A linear offline approximation algorithm C-NF is presented to solve the SBPP problem. It is proved that the C-NF algorithm has an asymptotic worst-case performance ratio of 2, which is independent of the size of start-up space. And the experimental average-case performances of C-NF are given. Also, the online property of SBPP is studied. It is pointed out that most of the classic online algorithms cannot offer definite worst-case performance ratios when applied on SBPP. And an online algorithm is proposed with a finite asymptotic worst-case performance ratio for any start-up space.

关 键 词：装箱问题 组合优化 近似算法 最坏情况渐近性能比 平均性能比 计算机 

分 类 号：O22[理学—运筹学与控制论] TP301.6[理学—数学]