Harvesting energy from environmental sources such as solar and wind can mitigate or solve the limited-energy problem in wireless sensor networks. In this paper, we propose an energy-harvest-aware route-selection method that incorporates harvest availability properties and energy storage capacity limits into the routing decisions. The harvest-aware routing problem is formulated as a linear program with a utility-based objective function that balances the two conflicting routing objectives of maximum total and maximum minimum residual network energy. The simulation results show that doing so achieves a longer network lifetime, defined as the time-to-first-node-death in the network. Additionally, most existing energy-harvesting routing algorithms route each traffic flow independently from each other. The LP formulation allows for a joint optimization of multiple traffic flows. Better residual energy statistics are also achieved by such joint consideration compared to independent optimization of each commodity. Harvesting energy from environmental sources such as solar and wind can mitigate or solve the limited-energy problem in wireless sensor networks. In this paper, we propose an energy-harvest-aware route-selection method that incorporates harvesting properties and energy storage capacity limits into the routing decisions. The harvest-aware routing problem is formulated as a linear program with a utility-based objective function that balances the two conflicting routing objectives of maximum total and maximum minimum residual network energy. The simulation results show that doing so achieves a longer network lifetime, defined as the time-to-first-node-death in the network. Additionally, most existing energy-harvesting routing algorithms route each traffic flow independently from each other. The LP formulation allows for a joint optimization of multiple traffic flows Better residual energy statistics are also achieved by such joint advice compared to independent optimizat ion of each commodity.