The　purpose　of　this　paper　is　to　construct　a　set　of　dynamic　and　multi-dimensional　sustainable　tourism　system　through　computer　related　technology　to　address　the　problems　related　to　tourism.　In　the　early　stage　of　model　construction,　relevant　data　are　collected　and　pre-processed　scientifically　with　the　help　of　data　collection　and　processing　technology,　and　presented　intuitively　through　data　visualization　technology.　In　the　research　process,　two　core　models　are　established:　Model　1　is　a　dynamic　multi-objective　framework　for　sustainable　tourism　optimization,　which　adopts　a　weighted　multi-objective　dynamic　optimization　algorithm　to　accurately　identify　the　sub-factors　affecting　income,　environmental　protection　and　tourists＇　satisfaction,　construct　a　reasonable　weighted　objective　function,　and　solve　it　by　using　the　Sequential　Least　Squares　Planning　(SLSQP)　algorithm,　so　that　the　optimal　number　of　tourists,　such　as　the　annual　number　of　1.7　million　tourists,　the　estimated　annual　income　of　390　million　U.S.　dollars,　and　so　on,　can　be　obtained.　Its　annual　revenue　is　390　million　dollars.　Meanwhile,　the　expenditure　plan　is　incorporated　into　the　model,　and　the　algorithm　enables　dynamic　simulation　and　further　optimization　in　subsequent　years.　Model　2　is　a　multi-objective　optimization　model　based　on　the　commercial　district,　which　uses　web　crawler　technology　to　capture　coordinate　data　and　combines　with　the　SLSQP　algorithm　to　determine　the　optimal　point,　and　after　optimization,　the　distance　between　the　facility　and　the　residential　area　is　increased　by　15.3%,　the　distance　between　the　facility　and　the　attraction　is　reduced　by　12.8%,　and　the　distance　between　the　facilities　is　reduced　by　10.4%.　Using　20　sets　of　urban　data,　the　random　forest　regression　algorithm　is　applied　to　model　1　to　generate　heat　map　and　coefficient　matrix　to　visualize　the　influence　of　each　factor　on　the　objective　function,　so　as　to　verify　the　applicability　of　the　model.　The　dynamic,　multi-perspective　sustainable　tourism　model　constructed　based　on　the　multi-objective　optimization　algorithm　effectively　balances　the　optimization　factors　in　various　aspects,　provides　a　solution　based　on　computer　technology　for　solving　the　over-tourism　problem　in　cities　like　Juno,　and　provides　powerful　data　support　and　technical　guarantee　for　governmental　decision-making　in　optimizing　the　number　of　tourists　and　the　layout　of　facilities,　dynamic　prediction　and　promotion　of　long-term　development,　and　has　high　application　potential　and　popularization　value.　It　can　provide　powerful　data　support　and　technical　guarantee　for　governmental　decision-making　in　optimizing　the　number　of　tourists　and　the　layout　of　facilities　and　promoting　long-term　development.　©　2025　IEEE.