AN IMPROVED CONVEX 0-1 QUADRATIC PROGRAM REFORMULATION FOR CHANCE-CONSTRAINED QUADRATIC KNAPSACK PROBLEMS

Shuhui Ji (), Xiaojin Zheng () and Xiaoling Sun ()
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Shuhui Ji: Department of Research and Development, Bank of Communications, No. 18 Xianxia Road, Shanghai 200336, P. R. China
Xiaojin Zheng: School of Economics and Management, Tongji University, Shanghai 200092, P. R. China
Xiaoling Sun: Department of Management Science, School of Management, Fudan University, Shanghai 200433, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2013, vol. 30, issue 03, 1-17

Abstract: We consider a chance-constrained quadratic knapsack problem (CQKP) where each item has a random size that is finitely distributed. We present a new convex 0-1 quadratic program reformulation for CQKP. This new reformulation improves the existing reformulation for general 0-1 quadratic program based on diagonal perturbation in the sense that the continuous relaxation of the new reformulation is tighter than or at least as tight as that of the existing reformulation. The improved reformulation is derived from a general matrix decomposition of the objective function and piecewise linearization of 0-1 variables. We show that the optimal parameters in the improved reformulation can be obtained by solving an SDP problem. Extension to k-item probabilistic quadratic knapsack problems is also discussed. Preliminary comparison results are reported to demonstrate the effectiveness of the improved reformulation.

Keywords: Stochastic programming; chance-constrained quadratic knapsack problem; finite discrete distribution; convex 0-1 quadratic program reformulation; SDP formulation (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1142/S0217595913400095

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