Optimization Online


The Multidimensional Knapsack Problem: Structure and Algorithms

Jakob Puchinger(jakobp***at***csse.unimelb.edu.au)
Guenther R. Raidl(raidl***at***ads.tuwien.ac.at)
Ulrich Pferschy(pferschy***at***uni-graz.at)

Abstract: We study the multidimensional knapsack problem, present some theoretical and empirical results about its structure, and evaluate different Integer Linear Programming (ILP) based, metaheuristic, and collaborative approaches for it. We start by considering the distances between optimal solutions to the LP-relaxation and the original problem and then introduce a new core concept for the MKP, which we study extensively. The empirical analysis is then used to develop new concepts for solving the MKP using ILP-based and memetic algorithms. Diff erent collaborative combinations of the presented methods are discussed and evaluated. Further computational experiments with longer run-times are also performed in order to compare the solutions of our approaches to the best known solutions of another so far leading approach for common MKP benchmark instances. The extensive computational experiments show the e ectiveness of the proposed methods, which yield highly competitive results in signi cantly shorter run-times than previously described approaches.

Keywords: multidimensional knapsack problem; integer linear programming; heuristics

Category 1: Integer Programming (0-1 Programming )

Category 2: Combinatorial Optimization (Meta Heuristics )

Citation: accepted for publication in: INFORMS Journal on Computing.

Download: [PDF]

Entry Submitted: 03/19/2009
Entry Accepted: 03/19/2009
Entry Last Modified: 03/19/2009

Modify/Update this entry

  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository


Coordinator's Board
Classification Scheme
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society