Abstract: The timed influence nets arc an emerging formalism which helps a system modcler in connecting a set of ac- tionable events and a set of desired effects through chains of cause and effect relationships in a complex uncertain situa- lion. The objective is to assess the behavior of the variables of interest as a function of both the timing of actions and the receipt of evidence on indicators, thus providing aid to decision makers in the revision of the planned courses of actions. This paper proposes an Simulated Annealing Algorithm (SA) based approach integrating standard Particle Swarm Opti- mization (PSO) for finding effective courses of action (CO八、).PSO is used in specified period at first, then employs S八 to initialize again for avoiding dropping the local best, and the arithmetic is executed iteratively until the ending condi- lion is satisfied. For the sake of efficiency, we arc going implement the arithmetic using MPI. hhe results suggest the approach appears to work well in uncertain situation.

Key words: Timed influence nets, Course of action, Effects based operations, Simulated annealing, Particle swarm optimization, MPI