There is an increasing interest regarding Unmanned Combat Air Vehicles (UCAVs) in recent years. These vehicles are designed to perform dangerous missions, such as eliminating enemy targets, which would otherwise put human life in danger. The problem of assigning tasks (e.g. classify, attack, and verification tasks for a target) to a group of UCAVs is a very challenging problem. Based on our observations of prior work, we propose and evaluate advanced task assignment scenarios that employ two new objectives using Integer Linear Programming (ILP). The first objective is the Overall Minimum Weapon Cost Objective, which ensures the minimum weapon cost task assignment considering the weapon requirements for each target type and the cost of each weapon type. The second objective is the Survivability Objective, which maximizes the number of vehicles still having payloads on board after a mission is completed. This ensures that future missions can be carried out using as many UCAVs as possible. In addition to these two objectives, we also propose several innovative contributions to task assignment scenarios including handling targets of different types in the same mission, determining weapon requirements for each type of target, assigning priorities to the target types, enabling a UCAV to carry more than one type of weapon, and setting constraints which allow a UCAV to use its specific weapons against specific target types. Experimental results from our implementation using a commercial ILP solver and various attack scenarios show the feasibility and effectiveness of our approach.