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The advancement of optical network technologies has enabled data-intensive e-science collaborations, which often require the transfer of large files with predictable performance. To support such applications, we design and evaluate two algorithms for scheduling time-constrained bulk transfers on wavelength-based optical research networks. The first one seeks to maximize the network throughput while maintaining a level of fairness among the jobs. The second algorithm works in an overloaded network and serves as an alternative to the first algorithm. It seeks to extend the end times by the smallest possible proportion and complete all the jobs by the extended end times. The main challenge is that the underlying problems are integer optimization problems for wavelength assignment, which have no known fast optimal solutions. We present a heuristic sub-algorithm called LPDAR, which converts fractional solutions from linear programming into integer solutions. LPDAR is the key component used in both aforementioned algorithms. Evaluation shows that LPDAR leads to very good algorithms with a performance level and speed both comparable to those of the LP fractional solutions.