This paper addresses the development of algorithms for the dynamic assignment of multiple, strongly coupled tasks in cooperative decision and control of a distributed UAV team. A symmetric vehicle-target scenario is considered with extensive task precedence and timing constraints. Moreover, strong coupling of task assignment with task planning can lead to in- feasible solutions. A suite of algorithms to address the scenario is presented. These algorithms are analyzed with respect to feasibility, optimality, strength and type of coupling that can be accommodated, required communications, and degree of decentralization. Algorithms discussed include: mixed integer linear programming, auction based optimization, constraint satisfaction based feasibility enforcement, network ßow, and hybrid techniques with heuristics. Analysis has revealed that, for strongly coupled tasks, decentralized solutions are not necessarily better than centralized solutions, unless communication costs are low.