This　paper　investigates　a　new　lane　reservation　problem　with　task　merging　that　consists　of　optimally　determining　which　lanes　in　a　transportation　network　have　to　be　reserved　and　designing　reserved　lane-based　routes　in　the　network　for　time-crucial　transport　tasks.　Part　of　the　tasks　whose　destinations　are　geographically　close　is　merged　to　reduce　the　number　of　vehicles　and　transport　costs.　Reserved　lanes　can　reduce　the　travel　time　of　task　vehicles　passing　through　them,　while　they　will　generate　negative　impact　on　normal　traffic,　such　as　traffic　delay　to　the　vehicles　on　adjacent　non-reserved　lanes.　The　objective　is　to　minimize　the　total　negative　impact　of　all　reserved　lanes.　For　this　problem,　two　new　integer　linear　programming　(ILP)　models　are　first　developed.　The　complexity　of　the　problem　is　proved　to　be　NP-hard.　Since　commercial　solver　(like　CPLEX)　is　time-consuming　for　solving　it　when　the　problem　size　increases,　a　fast　and　effective　improved　differential　evolution　algorithm　(IDEA)　is　developed　based　on　explored　problem　properties.　Extensive　experimental　results　for　a　real-life　case　and　benchmark　instances　of　up　to　500　nodes　in　the　network　and　30　transport　tasks　show　the　favorable　performance　of　the　IDEA,　as　compared　to　CPLEX,　differential　evolution　algorithm　and　genetic　algorithm.　Management　insights　are　also　drawn　to　support　practical　decision-making.