Computational Optimization and Applications

, Volume 56, Issue 1, pp 97–111 | Cite as

Algorithmic improvements on dynamic programming for the bi-objective {0,1} knapsack problem

  • José Rui Figueira
  • Luís Paquete
  • Marco Simões
  • Daniel Vanderpooten
Article

Abstract

This paper presents several methodological and algorithmic improvements over a state-of-the-art dynamic programming algorithm for solving the bi-objective {0,1} knapsack problem. The variants proposed make use of new definitions of lower and upper bounds, which allow a large number of states to be discarded. The computation of these bounds are based on the application of dichotomic search, definition of new bound sets, and bi-objective simplex algorithms to solve the relaxed problem. Although these new techniques are not of a common application for dynamic programming, we show that the best variants tested in this work can lead to an average improvement of 10 to 30 % in CPU-time and significant less memory usage than the original approach in a wide benchmark set of instances, even for the most difficult ones in the literature.

Keywords

Bi-objective 0-1 knapsack problems Multi-objective combinatorial optimization Bounds sets Dichotomic search Bi-objective simplex algorithm 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • José Rui Figueira
    • 1
  • Luís Paquete
    • 2
  • Marco Simões
    • 2
  • Daniel Vanderpooten
    • 3
  1. 1.CEG-IST, Center for Management Studies, Instituto Superior TécnicoTechnical University of LisbonPorto SalvoPortugal
  2. 2.CISUC, Department of Informatics EngineeringUniversity of CoimbraCoimbraPortugal
  3. 3.University Paris-DauphineParis Cedex 16France

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