We first formally define a model of a concurrent hierarchical plan, its execution, and its interactions (Section 2). Next, we describe summary information for propositional states and metric resources, mechanisms determining whether particular interactions must or may hold based on this information, and algorithms for deriving the information (Section 3). Built upon these algorithms are others for using summary information to determine whether a set of CHiPs must or might execute successfully under a set of ordering constraints (Section 4). These in turn are used within a sound and complete multilevel planning/coordination algorithm that employs search techniques and heuristics to efficiently navigate and prune the search space during refinement (Section 5). We then show how planning, scheduling, or coordinating at abstract levels can exponentially improve the performance of search and execution (Section 6). We provide experimental results demonstrating that the search techniques also greatly reduce the search for optimal solutions (Section 7). Finally, in Section 8 we differentiate our approach from related work that we did not mention elsewhere and conclude.