To　achieve　a　better　partitioning　of　VLSI　circuit,　re-clustering　and　discrete　optimization　are　applied　to　the　k-way　partitioning　algorithm.　Firstly,　re-clustering　is　used　to　reduce　the　scale　of　hypergraph,　i.e.,　the　rating　function　value　between　two　vertices　is　calculated　according　to　the　given　partitionings,　and　vertices　are　clustered　according　to　the　magnitude　of　the　rating　function　values.　Secondly,　the　hypergraph　is　converted　to　a　star　graph,　and　the　k-way　partitioning　problem　is　transformed　to　an　unconstrained　discrete　optimization　problem.　In　turn,　an　algorithm　is　designed　to　iteratively　move　the　vertices　with　the　largest　gain.　During　the　solution　process,　the　balancing　constraints　are　relaxed,　allowing　a　solution　to　be　temporarily　in　the　infeasible　region,　which　expands　the　solution　space　of　the　problem.　The　proposed　algorithm,　hMETIS-Kway　and　KaHyPar-K　are　tested　on　the　same　platform　on　the　ISPD98　test　benchmarks,　and　the　min-cut　and　running　time　are　compared.　Experimental　results　show　that,　the　proposed　algorithm　is　superior　to　hMETIS-Kway,　especially　when　k=2,　for　which　the　min-cut　is　reduced　by　0.173　and　the　runtime　is　sped　up　by　0.706.　The　proposed　algorithm　has　almost　the　same　improvement　effect　over　KaHyPar-K.　©　2024　Institute　of　Computing　Technology.　All　rights　reserved.