In　Australia,　Bioenergy　plays　an　important　role　in　modern　power　systems,　where　many　biomass　resources　provide　greenhouse　gas　neutral　and　electricity　at　a　variety　of　scales.　By　2050,　the　Biomass　energy　is　projected　to　have　a　40-50　%　share　as　an　alternative　source　of　energy.　In　addition　to　conversion　of　biomass,　barriers　and　uncertainties　in　the　production,　supply　may　hinder　biomass　energy　development.　The　sugarcane　is　an　essential　ingredient　in　the　production　of　Bioenergy,　across　the　whole　spectrum　ranging　from　the　first　generation　to　second　generation,　e.g.,　production　of　energy　from　the　lignocellulosic　component　of　the　sugarcane　initially　regarded　as　waste　(bagasse　and　cane　residue).　Sustainable　recovery　of　the　Lignocellulosic　component　of　sugarcane　from　the　field　through　a　structured　process　is　largely　unknown　and　associated　with　high　capital　outlay　that　have　stifled　the　growth　of　bioenergy　sector.　In　this　context,　this　paper　develops　a　new　scheduler　to　optimise　the　recovery　of　lignocellulosic　component　of　sugarcane　and　cane,　transport　and　harvest　systems　with　reducing　the　associated　costs　and　operational　time.　An　Optimisation　Algorithm　called　Limited　Discrepancy　Search　has　been　adapted　and　integrated　with　the　developed　scheduling　transport　algorithms.　The　developed　algorithms　are　formulated　and　coded　by　Optimization　Programming　Language　(OPL)　to　obtain　the　optimised　cane　and　cane　residues　transport　schedules.　Computational　experiments　demonstrate　that　high-quality　solutions　are　obtainable　for　industry-scale　instances.　To　provide　insightful　decisions,　sensitivity　analysis　is　conducted　in　terms　of　different　scenarios　and　criteria.　(C)　2018　Growing　Science　Ltd.　All　rights　reserved