We address the problem of planning the placement of a rigid object with a dual-arm robot in a cluttered environment. In this task, we need to locate a collision-free pose for the object that (a) facilitates the stable placement of the object, (b) is reachable by the robot, and (c) optimizes a user-given placement objective. In addition, we need to select which robot arm to use for the placement. To solve this task, we propose an anytime algorithm that integrates sampling-based motion planning with a novel hierarchical search for suitable placement poses. Our algorithm incrementally produces approach motions to stable placement poses, reaching placements with better objectives as runtime progresses. We evaluate our approach for two different placement objectives and observe its effectiveness even in challenging scenarios.