Parallel Simulated Annealing Algorithms

Simulated annealing (SA) has been considered a good tool for complex nonlinear optimization problems. The technique has been widely applied to a variety of problems. However, a major disadvantage of the technique is that it is extremely slow and hence not suitable for complex optimization problems such as scheduling. There are many attempts to develop parallel versions of the algorithm. Many of these algorithms are problem dependent in nature. We present, in this paper, two general algorithms for SA. The algorithms have been applied to job shop scheduling problem (JSS) and the traveling salesman problem (TSP) and it has been observed that it is possible to achieve superlinear speedups using the algorithm.