Resource leveling optimization of network scheduling under probabilistic time and cost

The optimization of Network Scheduling concerning the fixed completion time-resource leveling was studied. The time and cost of Network Scheduling activities are probabilistic, and the time-cost model isn't uniform distribution. A Monte-Carlo simulation model of Network Scheduling was established, and simulation output data of time and cost were analyzed. The methods for statistical analysis of getting a representative sample were studied. A Determinate Network Scheduling was constructed according to the representative sample of the simulation output data. The time-cost model of the determinate Network Scheduling activities was assumed as Weibull distribution, and a multi-apex Weibull time-cost model was presented counting the cost of every activity in the same time during the life time. Finally, the heuristic method of leveling resource need peak was studied, and a more leveling time-cost distribution model was gained.