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Development of a hybrid dynamic programming approach for solving discrete nonlinear knapsack problems

Ghassemi Tari, F ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. DOI: 10.1016/j.amc.2006.10.067
  3. Publisher: 2007
  4. Abstract:
  5. A multiple-choice knapsack problem can be formulated as a discrete nonlinear knapsack problem (DNKP). A powerful method for solving DNKP is the dynamic programming solution approach. The use of this powerful approach however is limited since the growth of the number of decision variables and state variables requires an extensive computer memory storage and computational time. In this paper we developed a hybrid algorithm for improving the computational efficiency of the dynamic programming when it is applied for solving the DNKP. In the hybrid algorithm, three routines of the imbedded state, surrogate constraints, and bounding scheme are incorporated for increasing the efficiency of this solution approach. We then conducted an experimental study for comparing the computational efficiency of the hybrid algorithm with the imbedded state dynamic programming approach. © 2006 Elsevier Inc. All rights reserved
  6. Keywords:
  7. Algorithms ; Computational efficiency ; Data storage equipment ; Nonlinear equations ; Problem solving ; Decision variables ; Discrete nonlinear knapsack problem (DNKP) ; Imbedded state ; Surrogate constraints ; Dynamic programming
  8. Source: Applied Mathematics and Computation ; Volume 188, Issue 1 , 2007 , Pages 1023-1030 ; 00963003 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0096300306014500