In　the　context　of　large　group　decision-making　(LGDM),　the　opinions　of　individuals　can　influence　each　other　due　to　their　trust　relationships.　So,　trust　relationships　should　be　deemed　as　just　as　important　as　evaluation　information,　and　they　should　be　considered　jointly　throughout　the　LGDM.　This　study　first　transforms　the　trust　relationships　between　decision-makers　into　an　information　type,　labeled　as　compromise　information,　whose　form　is　the　same　as　the　evaluation　information.　The　compromise　information　is　utilized　to　incorporate　trust　relationships　into　various　stages　of　the　decision-making　process,　including　clustering,　weight　determination,　consensus　reaching,　and　alternative　selection.　In　the　expert　clustering　and　weight　determination　processes,　more　criteria　and　factors　are　considered　by　considering　the　compromise　information.　In　the　consensus　reaching　process,　an　optimization　model　is　built　to　adjust　the　evaluation　information　of　clusters　to　simultaneously　guarantee　a　substantial　increase　in　the　global　consensus　level　and　minimize　the　adjustment　cost.　The　compromise　information　also　serves　as　a　reference　to　limit　the　range　of　the　adjusted　information.　An　objective　method　to　determine　the　consensus　threshold　is　proposed.　The　proposed　method　is　validated　through　an　application　example　and　comparisons,　demonstrating　its　rationality　and　effectiveness.　Simulation　results　indicate　that　the　proposed　consensus　reaching　method　converges　regardless　of　the　number　of　experts,　alternatives,　and　criteria.　The　proposed　method　integrates　evaluation　information　and　trust　relationships　into　the　LGDM　process,　thereby　improving　the　rationality　and　scientificity　of　the　decision　results.