A goal-driven approach to the 2D bin packing and variable-sized bin packing problems
被引:33
|
作者:
Wei, Lijun
论文数: 0引用数: 0
h-index: 0
机构:
City Univ Hong Kong, Dept Management Sci, Kowloon Tong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China
Wei, Lijun
[3
]
Oon, Wee-Chong
论文数: 0引用数: 0
h-index: 0
机构:
Ngee Ann Polytech, Sch InfoComm Technol, Singapore 599489, SingaporeHong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China
Oon, Wee-Chong
[2
]
Zhu, Wenbin
论文数: 0引用数: 0
h-index: 0
机构:
Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China
Zhu, Wenbin
[1
]
Lim, Andrew
论文数: 0引用数: 0
h-index: 0
机构:
City Univ Hong Kong, Dept Management Sci, Kowloon Tong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China
Lim, Andrew
[3
]
机构:
[1] Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China
[2] Ngee Ann Polytech, Sch InfoComm Technol, Singapore 599489, Singapore
[3] City Univ Hong Kong, Dept Management Sci, Kowloon Tong, Hong Kong, Peoples R China
Packing;
2D bin packing;
Goal-driven search;
Best-fit heuristic;
ALGORITHMS;
D O I:
10.1016/j.ejor.2012.08.005
中图分类号:
C93 [管理学];
学科分类号:
12 ;
1201 ;
1202 ;
120202 ;
摘要:
In this paper, we examine the two-dimensional variable-sized bin packing problem (2DVSBPP), where the task is to pack all given rectangles into bins of various sizes such that the total area of the used bins is minimized. We partition the search space of the 2DVSBPP into sets and impose an order on the sets, and then use a goal-driven approach to take advantage of the special structure of this partitioned solution space. Since the 2DVSBPP is a generalization of the two-dimensional bin packing problem (2DBPP), our approach can be adapted to the 2DBPP with minimal changes. Computational experiments on the standard benchmark data for both the 2DVSBPP and 2DBPP shows that our approach is more effective than existing approaches in literature. (C) 2012 Elsevier B.V. All rights reserved.