A new lower bound for the linear knapsack problem with general integer variables |
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Authors: | Kamlesh Mathur Prahalad Venkateshan |
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Affiliation: | Department of Operations, Weatherhead School of Management, Case Western Reserve University, Cleveland, OH 44106, United States |
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Abstract: | It is well known that the linear knapsack problem with general integer variables (LKP) is NP-hard. In this paper we first introduce a special case of this problem and develop an O(n) algorithm to solve it. We then show how this algorithm can be used efficiently to obtain a lower bound for a general instance of LKP and prove that it is at least as good as the linear programming lower bound. We also present the results of a computational study that show that for certain classes of problems the proposed bound on average is tighter than other bounds proposed in the literature. |
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Keywords: | Discrete optimization Integer programming Knapsack problem |
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