Graph and hypergraph partitioning have many important applications in various areas such as VLSI layout, mapping, and graph theory. For graph and hypergraph partitioning, there are very successful heuristics mainly based on Kernighan-Lin’s minimization technique. We propose two novel approaches for multiple-way graph and hypergraph partitioning. The proposed algorithms drastically outperform the best multiple-way partitioning algorithm both on randomly generated graph instances and on benchmark circuits. The proposed algorithms convey all the advantages of the algorithms based on KernighanLin’s minimization technique such as their robustness. However, they do not convey many disadvantages of those algorithms such as their poor performance on sparse test cases. The proposed algorithms introduce very interesting ideas that are also applicable to the existing algorithms without very much effort.