Operational route planning for second-generation bioenergy production integrating multiple value chains in horizontal collaboration

To ensure stable year-round production of second-generation bioenergy, a reliable and large supply volume of waste and residue feedstocks is essential. A collaborative supply from forestry residues (as primary source), agriculture waste, and municipal solid waste (MSW) can meet such demand and mitigate seasonal shortages and supply variations. However, these feedstocks are often spread over large geographical areas, making their transport costly and logistically challenging. Efficient transportation planning across the three sectors is therefore critical. Moreover, each sector plans transportation independently (independent fleet), using full truckload deliveries with different truck configurations. We propose a three-phase heuristics-optimization approach, using operations research tools, to integrate trucks routing across multiple sectors to supply a biorefinery efficiently (shared fleet). By sharing multi-configuration fleets while accounting for reconfiguration costs when trucks switch between specific feedstock types, transportation costs can be reduced significantly. Sharing a common fleet—where truck configurations are or can be made compatible with multiple feedstock types—furthermore enables more efficient full truckload delivery sequences and shorter travel distances. For instance, a container truck may transport agriculture residues as well as MSW or chipped wood from forest areas. We apply the proposed approach to a case study using data from Quebec, Canada. Results show that such truck sharing leads to an average 10% reduction in total costs, even after accounting for reconfiguration expenses. • Collaborative sourcing of biomass from the forestry, agriculture, and municipal solid waste sectors. • Integration of multi-configuration truck routing across the three sectors through truck sharing strategies. • Inclusion of different reconfiguration operations, such as truck cleaning, to enable efficient sharing of trucks. • Network simplification achieved through a three-phase heuristics-optimization approach. • Application to a medium-scale case study based on data from Quebec, Canada.