摘要：The collection of sawmill residuals is an important logistic activity for the pulp and paper industry, which use the biomass as a source of energy. We study a vehicle routing problem for a network composed of a single depot and 25 nearby sawmills in the Lower Mainland region of British Columbia, Canada. The sawmills serve as potential suppliers of residual biomass to the depot, which in turn processes and distributes the sawmill residuals to the pulp and paper mills. This problem consists of identifying the best daily routing schedule for a fixed number of vehicles. The objective is to maximize the ratio of residual dry tonnes collected to kilometers traveled, while achieving a minimum daily amount of residual dry mass. There are several random components in the problem, including the availability and moisture content of the residuals as well as the time spent on the road to retrieve the residuals. We use a combination of scenario analysis and heuristics to solve this stochastic vehicle routing problem (SPVRP).
关键词：renewable energy systemsrouting algorithmsrobust estimationuncertaintystochastic approximation
