In this paper a simulated annealing (SA) algorithm is presented for
the $0/1$ multidimensional knapsack problem. Problem-specific
knowledge is incorporated in the algorithm description and
evaluation of parameters in order to look into the performance of
finite-time implementations of SA. Computational results show that
SA performs much better than a genetic algorithm in terms of
solution time, whilst having a modest loss of solution quality.