A simulated annealing code for general integer linear programs

This paper explores the use of simulated annealing (SA) for solving arbitrary combinatorial optimisation problems. It reviews an existing code called GPSIMAN for solving 0-1 problems, and evaluates it against a commercial branch-and-bound code, OSL. The problems tested include travelling salesman, graph colouring, bin packing, quadratic assignment and generalised assignment. The paper then describes a technique for representing these problems using arbitrary integer variables, and shows how a general simulated annealing algorithm can also be applied. This new code, INTSA, outperforms GPSIMAN and OSL on almost all of the problems tested