Simulated annealing (SA) is a popular iterative heuristic used to solve a wide variety of combinatorial optimization problems. However, depending on the size of the problem, it may have large run-time requirements. One practical approach to speed up its execution is to parallelize it. In this paper we develop parallel SA schemes based on the asynchronous multiple-Markov chain model (AMMC) described in S.-Y. Lee and K. G. Lee (1996) and applied to standard-cell placement as presented in J. Chandy et al. (1997), The schemes are applied to solve the multi-objective standard cell placement problem using an inexpensive cluster-of-workstations environment. This problem requires the optimization of conflicting objectives (interconnect wire-length,...