Industrial　Wireless　Sensor　Networks　(IWSNs)　have　come　to　be　widely　used　for　collecting　industrial　information　due　to　their　low　cost,　rapid　deployment,　and　high　service　quality.　Clustering　sensors　together　extends　the　lifetime　of　IWSNs　is　an　essential　part　of　improving　their　energy　efficiency　and　network　stability.　In　this　paper,　we　propose　a　novel　Multi-Objective　Cluster　Head　Selection　Optimization　Model　(MOCHSOM)　to　improve　the　selection　of　cluster　heads　by　taking　into　account　multiple　factors　critical　to　the　IWSNs　lifetime.　Specifically,　our　model　minimizes　the　total　network　energy　consumption,　balances　the　network　cluster　energy　consumption,　and　maximizes　the　network　node　alive　time.　Moreover,　we　employ　an　Evolutionary　Algorithm　using　Reference-point　Based　Non-dominated　Sorting　Approach　(NSGA-III)　to　optimize　the　MOCHSOM　model　further.　The　experimental　results　show　that　our　proposed　algorithm　significantly　improves　the　network　lifetime　when　compared　with　conventional　clustering　algorithms.　©　2021　IEEE.