In　this　paper,　a　proximal　alternating　direction　method　of　multipliers　is　proposed　for　solving　a　minimization　problem　with　Lipschitz　nonconvex　constraints.　Such　problems　are　raised　in　many　engineering　fields,　such　as　the　analytical　global　placement　of　very　large　scale　integrated　circuit　design.　The　proposed　method　is　essentially　a　new　application　of　the　classical　proximal　alternating　direction　method　of　multipliers.　We　prove　that,　under　some　suitable　conditions,　any　subsequence　of　the　sequence　generated　by　the　proposed　method　globally　converges　to　a　Karush–Kuhn–Tucker　point　of　the　problem.　We　also　present　a　practical　implementation　of　the　method　using　a　certain　self-adaptive　rule　of　the　proximal　parameters.　The　proposed　method　is　used　as　a　global　placement　method　in　a　placer　of　very　large　scale　integrated　circuit　design.　Preliminary　numerical　results　indicate　that,　compared　with　some　state-of-the-art　global　placement　methods,　the　proposed　method　is　applicable　and　efficient.　©　2015,　Springer　Science+Business　Media　New　York.