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Approximation schemes for non-separable non-linear boolean programming problems under nested knapsack constraints

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  • Halman, Nir
  • Kellerer, Hans
  • Strusevich, Vitaly A.

Abstract

We consider a fairly general model of “take-or-leave” decision-making. Given a number of items of a particular weight, the decision-maker either takes (accepts) an item or leaves (rejects) it. We design fully polynomial-time approximation schemes (FPTASs) for optimization of a non-separable non-linear function which depends on which items are taken and which are left. The weights of the taken items are subject to nested constraints. There is a noticeable lack of approximation results on integer programming problems with non-separable functions. Most of the known positive results address special forms of quadratic functions, and in order to obtain the corresponding approximation algorithms and schemes considerable technical difficulties have to be overcome. We demonstrate how for the problem under consideration and its modifications FPTASs can be designed by using (i) the geometric rounding techniques, and (ii) methods of K-approximation sets and functions. While the latter approach leads to a faster scheme, the running times of both algorithms compare favorably with known analogues for less general problems.

Suggested Citation

  • Halman, Nir & Kellerer, Hans & Strusevich, Vitaly A., 2018. "Approximation schemes for non-separable non-linear boolean programming problems under nested knapsack constraints," European Journal of Operational Research, Elsevier, vol. 270(2), pages 435-447.
  • Handle: RePEc:eee:ejores:v:270:y:2018:i:2:p:435-447
    DOI: 10.1016/j.ejor.2018.04.013
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    References listed on IDEAS

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    1. Kellerer, Hans & Strusevich, Vitaly, 2013. "Fast approximation schemes for Boolean programming and scheduling problems related to positive convex Half-Product," European Journal of Operational Research, Elsevier, vol. 228(1), pages 24-32.
    2. Nir Halman & James B. Orlin & David Simchi-Levi, 2012. "Approximating the Nonlinear Newsvendor and Single-Item Stochastic Lot-Sizing Problems When Data Is Given by an Oracle," Operations Research, INFORMS, vol. 60(2), pages 429-446, April.
    3. Xu, Zhou, 2012. "A strongly polynomial FPTAS for the symmetric quadratic knapsack problem," European Journal of Operational Research, Elsevier, vol. 218(2), pages 377-381.
    4. Kabir Rustogi & Vitaly A. Strusevich, 2013. "Parallel Machine Scheduling: Impact of Adding Extra Machines," Operations Research, INFORMS, vol. 61(5), pages 1243-1257, October.
    5. Hans Kellerer & Ulrich Pferschy, 2004. "Improved Dynamic Programming in Connection with an FPTAS for the Knapsack Problem," Journal of Combinatorial Optimization, Springer, vol. 8(1), pages 5-11, March.
    6. Brahimi, Nadjib & Absi, Nabil & Dauzère-Pérès, Stéphane & Nordli, Atle, 2017. "Single-item dynamic lot-sizing problems: An updated survey," European Journal of Operational Research, Elsevier, vol. 263(3), pages 838-863.
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    8. T. Badics & E. Boros, 1998. "Minimization of Half-Products," Mathematics of Operations Research, INFORMS, vol. 23(3), pages 649-660, August.
    9. Nir Halman & Diego Klabjan & Mohamed Mostagir & Jim Orlin & David Simchi-Levi, 2009. "A Fully Polynomial-Time Approximation Scheme for Single-Item Stochastic Inventory Control with Discrete Demand," Mathematics of Operations Research, INFORMS, vol. 34(3), pages 674-685, August.
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    15. Qian, Fubin & Strusevich, Vitaly & Gribkovskaia, Irina & Halskau, Øyvind, 2015. "Minimization of passenger takeoff and landing risk in offshore helicopter transportation: Models, approaches and analysis," Omega, Elsevier, vol. 51(C), pages 93-106.
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    3. Nir Halman & Mikhail Y. Kovalyov & Alain Quilliot & Dvir Shabtay & Moshe Zofi, 2019. "Bi-criteria path problem with minimum length and maximum survival probability," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 469-489, June.

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