https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:12538 Sat 24 Mar 2018 08:17:30 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:12543 e for using arc e, an interval [l_e, u_e] (l_e, u_e ∈ ℤ) specifying the range of allowable resource consumption quantities along arc e, and a per-unit cost c_e for resource consumed along e. Furthermore, for each node n ∈ N, let U_n ∈ ℤ be the maximum amount of resource consumption a path can accumulate before visiting node n. Given a source node n_s ∈ N and sink node n_t ∈ N, the fixed-charge shortest-path problem (FCSPP) seeks to find a minimum-cost-feasible path from n_s to n_t . When resource consumption is simply additive, the resource-constrained shortest-path problem (RCSPP) is a special case of FCSPP. We develop a new dynamic programming algorithm for FCSPP. The algorithm uses solutions from labeling and dominance techniques for standard RCSPPs on slightly modified problems, and it combines these solutions by exploiting the structure provided by certain classes of knapsack problems to efficiently construct an optimal solution to FCSPP. Computational experiments demonstrate that our algorithm is often several orders of magnitude faster than naive dynamic programming procedures.]]> Sat 24 Mar 2018 08:17:04 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:18715 Sat 24 Mar 2018 08:01:05 AEDT ]]>