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A constraint satisfaction neural network and heuristic combined approach for concurrent activities scheduling |
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| Authors: | JiHong?Yan author-information" > author-information__contact u-icon-before" > mailto:yanjh@uwm.edu" title=" yanjh@uwm.edu" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author,Cheng?Wu |
| Affiliation: | (1) Department of Industrial Engineering and Manufacturing, University of Wisconsin, Milwaukee, USA;(2) Department of Automation, CIMS Center, Tsinghua University, 100084 Beijing, P.R. China |
| Abstract: | Scheduling activities in concurrent product development process is of great significance to shorten development lead time and minimize the cost. Moreover, it can eliminate the unnecessary redesign periods and giarantee that serial activities can be executed as concurrently as possible. This paper presents a constraint satisfaction neural network and heuristic combined approach for concurrent activities scheduling. In the combined approach, the neural network is used to obtain a feasible starting time of all the activities based on sequence constraints, the heuristic algorithm is used to obtain a feasible solution of the scheduling problem based on resource constraints. The feasible scheduling solution is obtained by a gradient optimization function. Simulations have shown that the proposed combined approach is efficient and feasible with respect to concurrent activities scheduling. |
| Keywords: | concurrent engineering product development process scheduling problem constraints satisfaction neural network heuristic |
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