Comparison of Heuristics for the 0–1 Multidimensional Knapsack Problem

Abstract

The multidimensional 0–1 knapsack problem (0–1MKP) is a generalization of the well-known 0–1 knapsack problem. As for any hard optimization problem also for 0–1MKP, a reasonable effort to cope with the problem is trying to derive heuristics which solve it suboptimally and which, possibly, yield a good trade-off between the solution quality and the time and the memory requirements. In this paper, we describe several heuristics for 0–1MKP. The first one is a simple multistage algorithm (SMA) which always maintains feasibility requirements. We also propose variants of the tabu search dealing with infeasibility, called also tunneling effect. We implement these heuristics as C code and compare their performances.