• DocumentCode
    3696047
  • Title

    Approximation Algorithms for the Generalized Multiple Knapsack Problems with K Restricted Elements

  • Author

    Binchao Huang;Jianping Li;Ko-Wei Lih;Haiyan Wang

  • Author_Institution
    Dept. of Math., Yunnan Univ., Kunming, China
  • Volume
    1
  • fYear
    2015
  • Firstpage
    470
  • Lastpage
    474
  • Abstract
    We are given a set of items, and a set of knapsacks. Both the weight and the profit of an item are functions of the knapsack, and each knapsack has a positive real capacity. A restriction is setting that the number of the items which are admissible to each knapsack is no more than k, and these items are taken as input for each knapsack. We consider two following objectives: (1) maximizing the total profit of all the knapsacks (Max-Sum k-GMK), (2) maximizing the minimum profit of all the knapsacks (Max-Min k-GMK). We show that the two problems are NP-complete when k is greater than or equal to 4. For the Max-Sum k-GMK problem, we can obtain a 1/2-approximation algorithm, and especially when k=2, we design an optimal algorithm. For the Max-Min k-GMK problem, we present a 1/ (k-1)-approximation algorithm, and especially when k=2, this algorithm is an optimal algorithm.
  • Keywords
    "Approximation algorithms","Algorithm design and analysis","Approximation methods","Bipartite graph","Artificial intelligence","Man machine systems"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2015 7th International Conference on
  • Print_ISBN
    978-1-4799-8645-3
  • Type

    conf

  • DOI
    10.1109/IHMSC.2015.149
  • Filename
    7334748