In this paper, we examine the multicriteria optimization involved in scheduling for data-path synthesis (DPS). The criteria we examine are the area cost of the components and schedule time. Scheduling for DPS is a well-known NP-complete problem. We present a method to find nondominated schedules using a combination of restricted search and heuristic scheduling techniques. Our method supports design with architectural constraints such as the total number of functional units, buses, etc. The schedules produced have been taken to completion using GABIND as written by Mandal et al., and the results are promising.