Scheduling activities in concurrent product development process is of great sig-nificance to shorten development lead time and minimize the cost. Moreover, it can eliminate theunnecessary redesign periods and guarantee that serial activities can be executed as concurrently aspossible. This paper presents a constraint satisfaction neural network and heuristic combined ap-proach for concurrent activities scheduling. In the combined approach, the neural network is usedto obtain a feasible starting time of all the activities based on sequence constraints, the heuris-tic algorithm is used to obtain a feasible solution of the scheduling problem based on resourceconstraints. The feasible scheduling solution is obtained by a gradient optimization function. Sim-ulations have shown that the proposed combined approach is efficient and feasible with respect toconcurrent activities scheduling.