Journal of the Operations Research Society of China ›› 2024, Vol. 12 ›› Issue (3): 795-807.doi: 10.1007/s40305-022-00393-w

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Maximizing the Differences Between a Monotone DR-Submodular Function and a Linear Function on the Integer Lattice

Zhen-Ning Zhang1, Dong-Lei Du2, Ran Ma3, Dan Wu4   

  1. 1 Department of Operations Research and Information Engineering, Beijing University of Technology, Beijing 100124, China;
    2 Faculty of Management, University of New Brunswick, Fredericton NB E3B 9Y2, Canada;
    3 School of Management Engineering, Qingdao University of Technology, Qingdao 266525, Shandong, China;
    4 School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, Henan, China
  • Received:2020-07-16 Revised:2021-11-18 Online:2024-09-30 Published:2024-08-15
  • Contact: Ran Ma, Zhen-Ning Zhang, Dong-Lei Du, Dan Wu E-mail:sungirlmr@163.com;zhangzhenning@bjut.edu.cn;ddu@unb.ca;lywd2964@126.com
  • Supported by:
    The first author is supported by the National Natural Science Foundation of China (Nos. 12001025 and 12131003). The second author is supported by the Natural Sciences and Engineering Research Council (No. 06446), and the National Natural Science Foundation of China (Nos. 11771386 and 11728104). The third author is supported by the National Natural Science Foundation of China (Nos. 11501171 and 11771251), and the Province Natural Science Foundation of Shandong (No. ZR2020MA028). The fourth author is supported by the National Natural Science Foundation of China (No. 11701150).

Abstract: In this paper, we investigate the maximization of the differences between a nonnegative monotone diminishing return submodular (DR-submodular) function and a nonnegative linear function on the integer lattice. As it is almost unapproximable for maximizing a submodular function without the condition of nonnegative, we provide weak (bifactor) approximation algorithms for this problem in two online settings, respectively. For the unconstrained online model, we combine the ideas of single threshold greedy, binary search and function scaling to give an efficient algorithm with a 1/2 weak approximation ratio. For the online streaming model subject to a cardinality constraint, we provide a one-pass ($3-\sqrt{5}$)/2 weak approximation ratio streaming algorithm. Its memory complexity is (klogk/ε), and the update time for per element is (log2k/ε).

Key words: Submodular maximization, DR-submodular, Integer lattice, Single-threshold greedy algorithm, Streaming algorithm

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