The growing integration of distributed generation (DG) is reshaping distribution network operation, making coordinated planning of network resources and consumer flexibility increasingly important. This study develops a hierarchical optimization framework that jointly considers DG allocation and demand response under time-of-use (TOU) pricing. The upper-level problem determines the location and capacity of DG units to improve network performance, while the lower-level problem captures consumer load adjustment in response to electricity prices. The bi-level formulation is converted into a single-level nonlinear optimization model using the Karush–Kuhn–Tucker conditions and solved by the Marine Predators Algorithm (MPA). The proposed framework is validated on IEEE 33-bus and 69-bus distribution systems and benchmarked against WOA, HHO, AOA, GBO, and SDO. Results show that MPA consistently provides the lowest daily energy loss, achieving 223.5 kWh/day and 241.7 kWh/day for the two test systems, respectively. It also delivers competitive TOU operating costs while maintaining all bus voltages within the 0.95 - 1.05 p.u. range. These findings demonstrate that coordinated DG planning and consumer flexibility can substantially improve the technical and economic performance of distribution systems compared with treating these decisions separately. The proposed framework therefore provides an effective and computationally practical approach for planning DG-integrated distribution networks under flexible electricity demand.