Abstract: The main objective of the weapon-target allocation problem (WTAP) is to achieve maximum survival of assets and maximum engagement of threats with the minimum number of resources such as weapons, ammunition, and human resources. The WTAP solution space is very large and complex with very large combinations of weapon type, ammunition type and number of rounds to be fired. Within the solution space, there may only be a few local minima and global minima. A very large number of iterations and execution time may be necessary when using conventional methods to identify optimum solutions within the solution space. This paper present a WTAP solution for mixed weapons. The weapon target ammunition data has been generated using Monte-Carlo simulation. An optimum solution has been estimated for a WTAP solution using a fuzzy approach—WTAP-Fuzzy. In addition to WTAP-Fuzzy, WTAP solutions using genetic algorithm (WTAP-GA); particle swarm optimization (WTAP-PSO); and simulated annealing (WTAP-SA) have been simulated and analysed and shown to have similar performance to WTAP-Fuzzy.