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
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