Title
Enhanced Branch-and-Bound Framework for a Class of Sequencing Problems
Abstract
In this paper, we propose an enhanced branch-and-bound (B&B) framework for a class of sequencing problems, which aim to find a permutation of all involved elements to minimize a given objective function. We require that the sequencing problems satisfy three conditions: 1) incrementally computable; 2) monotonic; and 3) overlapping subproblems. Our enhanced B&B framework is built on the classical B&B process by introducing two techniques, i.e., dominance rules and caching search states. Following the enhanced B&B framework, we conduct empirical studies on three typical and challenging sequencing problems, i.e., quadratic traveling salesman problem, traveling repairman problem, and talent scheduling problem. The computational results demonstrate the effectiveness of our enhanced B&B framework when compared to classical B&B and some exact approaches, such as dynamic programming and constraint programming. Additional experiments are carried out to analyze different configurations of the algorithm.
Year
DOI
Venue
2021
10.1109/TSMC.2019.2916202
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Keywords
DocType
Volume
Branch-and-bound (B&B),caching states,dominance rules,dynamic programming (DP),talent scheduling problem,traveling salesman/repairman problem
Journal
51
Issue
ISSN
Citations 
5
2168-2216
0
PageRank 
References 
Authors
0.34
24
5
Name
Order
Citations
PageRank
Zizhen Zhang110017.27
Luyao Teng2184.18
MengChu Zhou38989534.94
Jiahai Wang460449.01
Hua Wang5109077.62