Meta-RaPs approach for the 0-1 multidimensional Knapsack problem

  • Authors:
  • Reinaldo J. Moraga;Gail W. DePuy;Gary E. Whitehouse

  • Affiliations:
  • Department of Industrial Engineering, Universidad del Bío Bío, Avenida Collao 1202, Casilla 5C, Concepción, Chile;Department of Industrial Engineering, University of Louisville, Louisville, KY;Industrial Engineering and Management Systems Department, University of Central Florida, Orlando, FL

  • Venue:
  • Computers and Industrial Engineering - Special issue: Selected papers from the 31st international conference on computers & industrial engineering
  • Year:
  • 2005

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Abstract

A promising solution approach called Meta-RaPS is presented for the 0-1 Multidimensional Knapsack Problem (0-1 MKP). Meta-RaPS constructs feasible solutions at each iteration through the utilization of a priority rule used in a randomized fashion. Four different greedy priority rules are implemented within Meta-RaPS and compared. These rules differ in the way the corresponding pseudo-utility ratios for ranking variables are computed. In addition, two simple local search techniques within Meta-RaPS improvement stage are implemented. The Meta-RaPS approach is tested on several established test sets, and the solution values are compared to both the optimal values and the results of other 0-1 MKP solution techniques. The Meta-RaPS approach outperforms many other solution methodologies in terms of differences from the optimal value and number of optimal solutions obtained. The advantage of the Meta-RaPS approach is that it is easy to understand and easy to implement, and it achieves good results.