A simulated annealing code for general integer linear programs

This paper explores the use of simulated annealing (SA) for solving arbitrary combinatorialoptimisation problems. It reviews an existing code called GPSIMAN for solving0‐1 problems, and evaluates it against a commercial branch‐and‐bound code, OSL. Theproblems tested include travelling salesman, graph colouring, bin packing, quadratic assignmentand generalised assignment. The paper then describes a technique for representingthese problems using arbitrary integer variables, and shows how a general simulated annealingalgorithm can also be applied. This new code, INTSA, outperforms GPSIMAN andOSL on almost all of the problems tested.

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