Browsing by Author "Klampfl, Erica Zimmer"

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    A Mixed Integer Nonlinear Formulation for Improving Membrane Filtration Water Treatment Plant Design
    (2001-02) Klampfl, Erica Zimmer
    This thesis provides several contributions to the problem of building large-scale membrane filtration water treatment plants needed to meet increasingly stringent drinking water standards. The first contribution is an extension of a small-scale model of membrane filtration water treatment plants to a model that determines building specifications for the needed large-scale plants at a minimum cost. The large-scale model allows choosing a mix of feed and backflush pumps and partitioning the membrane area into more than one array in order to capture design decisions that can greatly reduce the cost. However, these additions to the model change the mathematical formulation from a small nonconvex nonlinear programming problem (NLP) to a large nonconvex mixed integer nonlinear programming problem (MINLP), which is much more difficult to solve. To address the difficulties associated with solving general nonconvex MINLPs, the second contribution is the development of an algorithm that exploits the structure of the nonconvex MINLP problem and the code written to implement the algorithm. The special structure of our nonconvex MINLP allows the development of a specific algorithm that exploits the structure and allows many benefits over existing methods. The algorithm guarantees termination to local optimizer for the MINLP, requires the solution of a small NLP and a relatively small IP compared to most algorithms that require the solution of a large NLP and a large MILP, requires the solution of an IP instead of an MILP, and requires very few iterations for termination. The MINLP is reformulated so that the algorithm needs only to iteratively solve alternations of an NLP and an integer programming problem (IP). Finally, we establish design guidelines for building large-scale membrane filtration water treatment plants. These guidelines include suggestions on how to choose an appropriate mix of feed and backflush pumps, how to partition the membrane area for different size plants, and how to estimate costs. Specifically, we show that larger plants can be operated more cost efficiently than smaller plants at higher recoveries and that a more flexible consideration of facility configuation and pump selection may reduce costs for larger plants by approximately 20% per year.
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    A mixed integer nonlinear formulation for improving membrane filtration water treatment plant design
    (2001) Klampfl, Erica Zimmer; Dennis, John E., Jr.
    This thesis provides several contributions to the problem of building large-scale membrane filtration water treatment plants needed to meet increasingly stringent drinking water standards. The first contribution is an extension of a small-scale model of membrane filtration water treatment plants to a model that determines building specifications for the needed large-scale plants at a minimum cost. The large-scale model allows choosing a mix of feed and backflush pumps and partitioning the membrane area into more than one array in order to capture design decisions that can greatly reduce the cost. However, these additions to the model change the mathematical formulation from a small nonconvex nonlinear programming problem (NLP) to a large nonconvex mixed integer nonlinear programming problem (MINLP), which is much more difficult to solve. To address the difficulties associated with solving general nonconvex MINLPs, the second contribution is the development of an algorithm that exploits the structure of the nonconvex MINLP problem and the code written to implement the algorithm. The special structure of our nonconvex MINLP allows the development of a specific algorithm that exploits the structure and allows many benefits over existing methods. The algorithm guarantees termination to local optimizer for the MINLP, requires the solution of a small NLP and a relatively small IP compared to most algorithms that require the solution of a large NLP and a large MILP, requires the solution of an IP instead of an MILP, and requires very few iterations for termination. The MINLP is reformulated so that the algorithm needs only to iteratively solve alternations of an NLP and an integer programming problem (IP). Finally, we establish design guidelines for building large-scale membrane filtration water treatment plants. These guidelines include suggestions on how to choose an appropriate mix of feed and backflush pumps, how to partition the membrane area for different size plants, and how to estimate costs. Specifically, we show that larger plants can be operated more cost efficiently than smaller plants at higher recoveries and that a more flexible consideration of facility configuration and pump selection may reduce costs for larger plants by approximately 20% per year.
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    Strategic Load Planning for Less-Than-Truckload Trucking
    (1999-06) Hoppe, Bruce; Klampfl, Erica Zimmer; McZeal, Cassandra; Rich, Jennifer
    Less-than-truckload trucking represents a portion of the motor carrier industry in which the shipments to be sent on trucks do not completely fill a 45,000 lb. volume tractor-trailer. Typically, the freight in each shipment weighs under 10,000 lbs., with a large majority falling under 1000 lbs. Since each shipment does not fill a truck, significant savings can be achieved by consolidating shipments into loads at regional terminals and transporting these loads from terminal to terminal. The goal of the strategic load planning problem is to determine how to route the flow of consolidated loads from origin terminals to destination terminals cost effectively and allowing for certain service standards. The actual gathering of these shipments at the origin terminal and the distribution of them from the destination terminal is handled in a separate problem commonly referred to as the pick-up and delivery problem. This overall method of distribution requires a network of terminals, the design of which is closely related to many classic network design problems. We have built a software system which, when given the appropriate data concerning a company's needs and past routing decisions, will build a network to solve the strategic load planning problem. The empirical results, based on real data from trucking companies, indicate that our system does a very credible job of building an efficient network.