No description available.

No description available.

The generation and maintenance of feasible schedules for Navy training courses are labor intensive throughout the Naval Education and Training Command. The major constraints affecting this scheduling are planned input requirements and the suitability/availability of instructors, equipment, and facilities. An additional constraint is that schedules must be established for the current year, updated and revised as necessary, and projected for the out-year planning requirements of the 5-Year Defense Plan. This thesis documents the essential components of scheduling for training at a representative training center, the Fleet Anti-Submarine Warfare Training Center, Pacific. It provides details for the automation of the current scheduling process, with a limited demonstration for a sample of courses. Conclusions and recommendations for the development of an automated optimal scheduling system are presented.

No description available.

The resource demand on embedded devices is constantly growing. This is caused by the sheer explosion of software based functions in embedded systems, that are growing far faster than the resources of the single-core and multi-core embedded processors. As one of the limitation is the computing power of the processors we need to explore ways to use this resource more efficiently. We identified that during the run-time of the embedded devices the resource demand of the software functions is permanently changing dependent on the device situation. To enable an embedded device to take advantage of this dynamic resource demand, the allocation of the software functions to the processor must be handled by a scheduler that is able to evaluate the resource demand of the software functions in relation to the device situation. This marks a change in embedded devices from static defined software systems to dynamic software systems. Above that we can increase the efficiency even further by extending the approach from a single device to a distributed or networked system (many-core system). However, existing approaches to deal with dynamic resource allocation are focused on individual devices and leave the optimization potential of manycore systems untouched. Our concept will extend the existing Hierarchical Asynchronous Multi-Core Scheduler (HAMS) concept for individual devices to many-core systems. This extension introduces a dynamic situation aware scheduler for many-core systems which take the current workload of all devices and the system-situation into account. With our approach, the resource efficiency of an embedded many-core system can be increased. The following paper will explain the architecture and the expected results of our concept.

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Master of Science / Department of Industrial & Manufacturing Systems Engineering / Todd W. Easton / Westside High School (WHS) of Omaha, Nebraska utilizes a novel scheduling system called Modular scheduling. This system offers numerous advantages over the standard school day in terms of student learning and faculty development. Modular Scheduling allows teachers to design the structure of their own classes by adjusting the frequency, duration and location of each of their daily lessons. Additionally, teachers are able combine their classes with those of other teachers and team-teach. Modular scheduling also allows for open periods in both students’ and teachers’ schedules. During this time, students are able to complete school work or seek supplemental instruction with a teacher who is also free. Teachers are able to use their open mods to plan, meet in teams and help students who have fallen behind. Currently, a semester’s class schedules are constructed over the course of a seven week period by a full-time employee using a computer program developed in FORTRAN®. The process is extremely tedious and labor intensive which has led to considerable wasted time, cost and frustration. This thesis presents a novel scheduling program called the SMART Scheduler that is able to do in seconds what previously took weeks to accomplish. Once parameters have been input, The SMART Scheduler is able to create cohesive class schedules within a modular environment in less than 6 seconds. The research presented describes the steps that were taken in developing the SMART Scheduler as well as computational results of its implementation using actual data provided by WHS. The goal of this research is to enable WHS and other schools to efficiently and effectively utilize modular scheduling to positively affect student learning.

by Lam Sze-sing. / "April 2000." / Thesis (Ph.D.)--Chinese University of Hong kong, 2000. / Includes bibliographical references 9p. 149-157). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Emerging technologies enable a set of distributed resources across a network to be linked together and used in a coordinated fashion to solve a particular parallel application at the same time. Such applications are often abstracted as directed acyclic graphs (DAGs), in which vertices represent application tasks and edges represent data dependencies between tasks. Effective scheduling mechanisms for DAG applications are essential to exploit the tremendous potential of computational resources. The core issues are that the availability and performance of resources, which are already by their nature heterogeneous, can be expected to vary dynamically, even during the course of an execution. In this thesis, we first consider the problem of scheduling DAG task graphs onto heterogeneous resources with changeable capabilities. We propose a list-scheduling heuristic approach, the Global Task Positioning (GTP) scheduling method, which addresses the problem by allowing rescheduling and migration of tasks in response to significant variations in resource characteristics. We observed from experiments with GTP that in an execution with relatively frequent migration, it may be that, over time, the results of some task have been copied to several other sites, and so a subsequent migrated task may have several possible sources for each of its inputs. Some of these copies may now be more quickly accessible than the original, due to dynamic variations in communication capabilities. To exploit this observation, we extended our model with a Copying Management(CM) function, resulting in a new version, the Global Task Positioning with copying facilities (GTP/c) system. The idea is to reuse such copies, in subsequent migration of placed tasks, in order to reduce the impact of migration cost on makespan. Finally, we believe that fault tolerance is an important issue in heterogeneous and dynamic computational environments as the availability of resources cannot be guaranteed. To address the problem of processor failure, we propose a rewinding mechanism which rewinds the progress of the application to a previous state, thereby preserving the execution in spite of the failed processor(s). We evaluate our mechanisms through simulation, since this allow us to generate repeatable patterns of resource performance variation. We use a standard benchmark set of DAGs, comparing performance against that of competing algorithms from the scheduling literature.

This thesis studies Production Scheduling in a multistage hybrid flowshop facility. It first states the general Production Planning and Scheduling problem and highlights some drawbacks of classical solutions. A theoretical decomposition-based approach is introduced whose main issue is to overcome non-efficient capacity utilization. By using Branch and Bound methods, an in-depth analysis of the scheduling part of the system is then carried out throughout the study and development of upper and lower bounds as well as branching schemes. Already-existing and new heuristics are presented and compared on different shop floor configurations. Five different heuristic approaches are studied. By scheduling the HFS one stage at a time the first approach uses different stage sequencing orders. The second and third approaches are mainly list heuristics. The second approach uses ideas derived from the multistage classical flowshop with a single machine per stage, while the third approach uses classical dispatching priority rules. The fourth and fifth approaches, respectively, use random scheduling and local search techniques. Statistical analysis is carried out in order to compare the heuristics and to select the best of them for each shop configuration. Already-existing and new lower bounds on the single stage subproblem are also presented and compared. Three new lower bounds are developed: a dual heuristic based bound, a partially preemptive bound and a heuristic for the so-called subset bound. Some of these lower bounds use a network flow algorithm. A new version of the “Preflow Push” algorithm which runs faster than the original one is presented. The best lower bounds are selected based on numerical tests. Two branch and bound algorithms are presented, an improved version of the sequence enumeration method and a generalization of the so-called interval branching method, along with several bounding strategies. Based on the upper and lower bound studies, several branch and bound algorithms are presented and compared using numerical tests on different shop floor configurations. Eventually, an Object Model for Scheduling Algorithm Implementations (OMSAI), that has been used for the computer implementation of the developed algorithms, is presented.