Highway　infrastructure　plays　an　important　role　in　assuring　the　proper　function　of　the　nation＇s　transportation.　Highway　alignment　is　an　essential　part　of　the　highway　planning　and　design　phase,　which　has　significant　effects　on　the　surroundings.　Identifying　optimal　highway　routes　while　using　traditional　methods　requires　significant　time,　cost,　and　effort,　since　it　requires　a　comprehensive　assessment　of　multiple　factors,　such　as　cost　and　environmental　impacts.　This　study　proposes　an　approach　for　managing　highway　alignment　in　the　context　of　a　larger　landscape　that　integrates　building　information　modelling　(BIM)　and　geographic　information　system　(GIS)　capabilities.　To　support　this　integration,　semantic　web　technologies　are　used　to　integrate　data　on　a　semantic　level.　Moreover,　the　approach　also　uses　genetic　algorithms　(GAs)　for　optimizing　highway　alignments.　A　fully　automated　model　is　developed　that　enables　data　interoperability　between　BIM　and　GIS　systems　and　also　allows　for　data　exchange　between　the　integration　model　and　the　optimization　algorithm.　The　model　enables　the　full　exploitation　of　features　of　the　project　and　its　surroundings　for　highway　alignment　planning.　The　proposed　model　is　also　applied　to　a　real　highway　project　to　validate　its　effectiveness.　The　visualization　model　of　the　highway　project　and　its　surroundings　provides　a　realistic　three-dimensional　image　that　produces　a　comprehensive　virtual　environment,　where　the　project　could　be　effectively　planned　and　designed.　That　can　help　to　reduce　design　errors　and　miscommunication,　which,　in　turn,　reduces　project　risks.　Moreover,　geological　and　geographical　analyses　help　to　identify　geohazards　and　environmentally　sensitive　regions.　The　proposed　model　facilitates　highway　alignment　planning　by　providing　a　cross-disciplinary　approach　to　close　the　gap　between　the　infrastructural　and　geotechnical　planning　processes.