On Johnson's two-machine flow shop with random processing times
Operations Research
The two-machine flowshop scheduling problem with total tardiness
Computers and Operations Research
Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
A new branch and bound algorithm for minimizing mean tardiness in two-machine flowshops
Computers and Operations Research
Flowshop scheduling with limited temporary storage
Journal of the ACM (JACM)
Scheduling Algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Minimizing tardiness in a two-machine flow-shop
Computers and Operations Research
Computers and Operations Research
An effective hybrid genetic algorithm for flow shop scheduling with limited buffers
Computers and Operations Research
On aggregate available bandwidth in many-to-one data transfer-modeling and applications
Multimedia Tools and Applications
Data & Knowledge Engineering
Computers and Operations Research
WCDMA and WLAN for 3G and beyond
IEEE Wireless Communications
Bandwidth estimation: metrics, measurement techniques, and tools
IEEE Network: The Magazine of Global Internetworking
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This study investigates sequence optimization of media objects in a multimedia presentation that is dynamically composed from digital libraries. Each media object can be associated with a due date. The aim is to schedule the media objects in a delay-prone network environment such that the overall presentation lag and the due date penalties of the media objects of presentations can be minimized. We formulate the sequencing problem with buffer constraints in the media player into a flowshop scheduling problem and present a reduction strategy with a branch and bound algorithm to derive optimal sequences. The algorithm can be applied in applications with up to a dozen objects to be scheduled. In addition, we propose a modified NEH-based heuristic algorithm which can provide approximate solutions with an average error rate of less than 4%. The computation-efficient heuristic, when deployed in applications with heavily loaded servers, can obtain near-optimal sequences for problems with more than a dozen objects. The proposed algorithms are embedded into a prototype system for providing digital library services.