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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Approximations with Improving Error Bounds for Makespan Minimization in Batch Manufacturing

Weyerman, Whitney Samuel 14 March 2008 (has links) (PDF)
Multipurpose batch manufacturing systems allow a suite of job types to be processed with a fixed set of machines. These types of systems are commonly found in chemical processing, as well as in computer systems and the service industry. In this thesis we consider the problem of sequencing jobs entering the manufacturing system in order to minimize makespan, or total time to complete processing of the jobs. We formulate this problem as a dynamic programming problem and illustrate the computational difficulty of solving this problem. We give a method for simulation of the system by representing each machine in the system as a finite state automata. This allows one to calculate the makespan given a manufacturing system and a sequence. Due to the complexity of the system, we offer an approximation to the problem. We show that the approximation strategy allows refinement. This progressive refinement of the approximation results in a sequence of approximations that approach the true problem. As the approximation is refined, the computational complexity of the approximated problem grows. For a simplified system, we show that the approximation has bounded error. Furthermore, we show that the error bound of the approximation sequence improves as the approximation approaches the true problem. This presents a trade-off between computational complexity and accuracy of the solution. A decision maker using this sequence of approximations can quickly determine a level of approximation based on the amount of computational power available and the accuracy needed in a solution.
2

Three Essays in Parallel Machine Scheduling

Garg, Amit January 2008 (has links)
No description available.
3

Integrating Combinatorial Scheduling with Inventory Management and Queueing Theory

Terekhov, Daria 13 August 2013 (has links)
The central thesis of this dissertation is that by combining classical scheduling methodologies with those of inventory management and queueing theory we can better model, understand and solve complex real-world scheduling problems. In part II of this dissertation, we provide models of a realistic supply chain scheduling problem that capture both its combinatorial nature and its dependence on inventory availability. We present an extensive empirical evaluation of how well implementations of these models in commercially available software solve the problem. We are therefore able to address, within a specific problem, the need for scheduling to take into account related decision-making processes. In order to simultaneously deal with combinatorial and dynamic properties of real scheduling problems, in part III we propose to integrate queueing theory and deterministic scheduling. Firstly, by reviewing the queueing theory literature that deals with dynamic resource allocation and sequencing and outlining numerous future work directions, we build a strong foundation for the investigation of the integration of queueing theory and scheduling. Subsequently, we demonstrate that integration can take place on three levels: conceptual, theoretical and algorithmic. At the conceptual level, we combine concepts, ideas and problem settings from the two areas, showing that such combinations provide insights into the trade-off between long-run and short-run objectives. Next, we show that theoretical integration of queueing and scheduling can lead to long-run performance guarantees for scheduling algorithms that have previously been proved only for queueing policies. In particular, we are the first to prove, in two flow shop environments, the stability of a scheduling method that is based on the traditional scheduling literature and utilizes processing time information to make sequencing decisions. Finally, to address the algorithmic level of integration, we present, in an extensive future work chapter, one general approach for creating hybrid queueing/scheduling algorithms. To our knowledge, this dissertation is the first work that builds a framework for integrating queueing theory and scheduling. Motivated by characteristics of real problems, this dissertation takes a step toward extending scheduling research beyond traditional assumptions and addressing more realistic scheduling problems.
4

Integrating Combinatorial Scheduling with Inventory Management and Queueing Theory

Terekhov, Daria 13 August 2013 (has links)
The central thesis of this dissertation is that by combining classical scheduling methodologies with those of inventory management and queueing theory we can better model, understand and solve complex real-world scheduling problems. In part II of this dissertation, we provide models of a realistic supply chain scheduling problem that capture both its combinatorial nature and its dependence on inventory availability. We present an extensive empirical evaluation of how well implementations of these models in commercially available software solve the problem. We are therefore able to address, within a specific problem, the need for scheduling to take into account related decision-making processes. In order to simultaneously deal with combinatorial and dynamic properties of real scheduling problems, in part III we propose to integrate queueing theory and deterministic scheduling. Firstly, by reviewing the queueing theory literature that deals with dynamic resource allocation and sequencing and outlining numerous future work directions, we build a strong foundation for the investigation of the integration of queueing theory and scheduling. Subsequently, we demonstrate that integration can take place on three levels: conceptual, theoretical and algorithmic. At the conceptual level, we combine concepts, ideas and problem settings from the two areas, showing that such combinations provide insights into the trade-off between long-run and short-run objectives. Next, we show that theoretical integration of queueing and scheduling can lead to long-run performance guarantees for scheduling algorithms that have previously been proved only for queueing policies. In particular, we are the first to prove, in two flow shop environments, the stability of a scheduling method that is based on the traditional scheduling literature and utilizes processing time information to make sequencing decisions. Finally, to address the algorithmic level of integration, we present, in an extensive future work chapter, one general approach for creating hybrid queueing/scheduling algorithms. To our knowledge, this dissertation is the first work that builds a framework for integrating queueing theory and scheduling. Motivated by characteristics of real problems, this dissertation takes a step toward extending scheduling research beyond traditional assumptions and addressing more realistic scheduling problems.

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