A Constraint Satisfaction Neural Network and Heuristic Combined Approach for Concurrent Activities Scheduling

Scheduling activities in concurrent productdevelopment process is of great significance to shorten developmentlead time and minimize the cost. Moreover, it can eliminate theunnecessary redesign periods and guarantee that serial activities canbe executed as concurrently as possible. This paper presents aconstraint satisfaction neural network and heuristic combined approachfor concurrent activities scheduling. In the combined approach, theneural network is used to obtain a feasible starting time of all theactivities based on sequence constraints, the heuristic algorithm isused to obtain a feasible solution of the scheduling problem based onresource constraints. The feasible scheduling solution is obtained by agradient optimization function. Simulations have shown that theproposed combined approach is efficient and feasible with respect toconcurrent activities scheduling.