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 [1] and applied to standard-cell placement in [2]. 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, power dissipation, and timing performance), and Fuzzy logic...