Knapsack problems with sigmoid utilities: Approximation algorithms via hybrid optimization

Vaibhav Srivastava and Francesco Bullo

European Journal of Operational Research, 2014, vol. 236, issue 2, 488-498

Abstract: We study a class of non-convex optimization problems involving sigmoid functions. We show that sigmoid functions impart a combinatorial element to the optimization variables and make the global optimization computationally hard. We formulate versions of the knapsack problem, the generalized assignment problem and the bin-packing problem with sigmoid utilities. We merge approximation algorithms from discrete optimization with algorithms from continuous optimization to develop approximation algorithms for these NP-hard problems with sigmoid utilities.

Keywords: Sigmoid utility/S-curve; Knapsack problem; Generalized assignment problem; Bin-packing problem; Multi-choice knapsack problem; Human attention allocation (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:236:y:2014:i:2:p:488-498

DOI: 10.1016/j.ejor.2013.12.035

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