Manufacturing companies must constantly improve productivity to respond to dynamic changes in customer demand in order to maintain their competitiveness and marketshares. This requires manufacturers to adopt more efficient methodologies to design and control their manufacturing systems. In recent decades, virtual cellular manufacturing (VCM), as an advanced manufacturing concept, has attracted increasing attention in the research community, because traditional cellular manufacturing is inadequate when operating in a highly dynamic manufacturing environment. Virtual cellular manufacturing temporarily and dynamically groups production resources to form virtual cells according to production requirements, thus enjoying high production efficiency and flexibility simultaneously. The objective of this research is to develop cost-effective methodologies for manufacturing cell formation and production scheduling in virtual cellular manufacturing systems (VCMSs), operating in single-period/multi-period, and dynamic manufacturing environments. In this research, two mathematical models are developed to describe the characteristics of VCMSs operating under a single-period and a multi-period manufacturing environment respectively. These models aim to develop production schedules to minimize the total manufacturing cost incurred in manufacturing products for the entire planning horizon, taking into consideration many practical constraints such as workforce requirements, effective capacities of production resources, and delivery due dates of orders. In the multi-period case, worker training is also considered and factors affecting worker training are analyzed in detail. This research also develops a novel hybrid algorithm to solve complex production scheduling problems optimally for VCMSs. The hybrid algorithm is based on the techniques of discrete particle swarm optimization, ant colony system and constraint programming. Its framework is discrete particle swarm optimization which can locate good production schedules quickly. To prevent the optimization process being trapped into a local optimum, concepts of ant colony system and constraint programming are incorporated into the framework to greatly enhance the exploration and exploitation of the solution space, thus ensuring better quality production schedules. Sensitivity analyses of the key parameters of the hybrid algorithm are also conducted in detail to provide a theoretical foundation which shows that the developed hybrid algorithm is indeed an excellent optimization tool for production scheduling in VCMSs. In practice, the occurrence of unpredictable events such as breakdown of machines, change in the status of orders and absenteeism of workers will make the current production schedule infeasible. A new feasible production schedule may therefore need to be generated rapidly to ensure smooth manufacturing operations. This research develops several cost-effective production rescheduling strategies for VCMSs operating under different dynamic manufacturing environments. These strategies facilitates the determination of when-to and how-to take rescheduling actions. To further enhance the performance of such strategies in generating new production schedules, especially for large-scale manufacturing systems, a parallel approach is established to implement the developed hybrid algorithm on GPU with compute unified device architecture. The convergence characteristics of the proposed hybrid algorithm are also studied theoretically by using probability theory and Markov chain model. The analysis results show that the optimization process will eventually converge to the global optimal solution. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Unlike traditional cellular networks, where voice calls dominate the network traffic, modern mobile traffic is created by of a mixture of both voice and broadband data services. The heterogeneous mixture of voice and data services in mobile broadband networks includes voice calls, web browsing, file transfers, video streaming, and social media applications. Consequently, network planning and radio resource management strategies must be aware of the quality of experience perceived by the users using various types of applications. In this report, we explore the traffic characteristics, scheduling and resource allocation strategies, and user experience models in mobile broadband networks. / text

Abstract—This paper proposes a new approach for the optimal integrated control and real-time scheduling of control tasks. First, the problem of the optimal integrated control and nonpreemptive off-line scheduling of control tasks in the sense of the H2 performance criterion is addressed. It is shown that this problem may be decomposed into two sub-problems. The first sub-problem aims at finding the optimal non-preemptive off-line schedule, and may be solved using the branch and bound method. The second sub-problem uses the lifting technique to determine the optimal control gains, based on the solution of the first sub-problem. Second, an efficient on-line scheduling algorithm is proposed. This algorithm, called Reactive Pointer Placement (RPP) scheduling algorithm, uses the plant state information to dispatch the computational resources in a way that improves control performance. Control performance improvements as well as stability guarantees are formally proven. Finally, simulations as well as experimental results are presented in order to illustrate the effectiveness of the proposed approach.

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published_or_final_version / abstract / Computer Science / Master / Master of Philosophy

published_or_final_version / abstract / toc / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

published_or_final_version / abstract / toc / Computer Science and Information Systems / Doctoral / Doctor of Philosophy

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Σκοπός της διπλωματικής εργασίας είναι η ανάπτυξη εργαλείου το οποίο θα δέχεται ως είσοδο C πρόγραμμα και θα βρίσκει όλη τη πληροφορία η οποία σχετίζεται με την επαναχρησιμοποίηση των δεδομένων. Τα δεδομένα αφορούν πίνακες μέσα σε βρόχους. Η επαναχρησιμοποίηση δεδομένων χωρίζεται σε τρεις κατηγορίες: α) Εύρεση της επαναχρησιμοποίησης για κάθε πίνακα ξεχωριστά. β) Εύρεση της επαναχρησιμοποίησης στοιχείων πίνακα που χρησιμοποιούνται σε διάφορες εκφράσεις. γ) Εύρεση χρήσης στοιχείων μεταξύ διαφορετικών πινάκων στην ίδια έκφραση. Η εύρεση των χαρακτηριστικών της επαναχρησιμοποίησης χρησιμεύει για την εύρεση αποδοτικού χρονοπρογραμματισμού (scheduling) του προγράμματος το οποίο θα έχει καλύτερη τοπικότητα (data locality). Η επαναχρησιμοποίηση δεδομένων εφαρμόζεται στο πρόβλημα πολλαπλασιασμού πίνακα επί διάνυσμα. Συμβατικές και μη τεχνικές υλοποίησης του προβλήματος έχουν συγκριθεί με τη προτεινόμενη. Η σύγκριση πραγματοποιήθηκε με τον εξομοιωτή SimpleScalar στον οποίο μπορούμε να τροποποιήσουμε την αρχιτεκτονική και σε υπολογιστή Desktop Pentium 4. / -

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