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   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Owen Deutsch and Duane S. Boning.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Dukellis, John N. (John Nicholas), 1977-</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science</dim:field>
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   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (leaves 87-88).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Linear and nonlinear assignment problems are addressed by the use of auction algorithms. The application of auction to the standard linear assignment problem is reviewed. The extension to nonlinear problems is introduced and illustrated with two examples. Techniques that are employed for model reduction include discretization, classification, and imposition of assignment constraints. The tradeoff between solution speed and optimality for the nonlinear problem is analyzed and demonstrated for the sample problem.</dim:field>
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   	&lt;Title>Applications of auction algorithms to complex problems with constraints&lt;/Title>
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   	&lt;Abstract>Linear and nonlinear assignment problems are addressed by the use of auction algorithms. The application of auction to the standard linear assignment problem is reviewed. The extension to nonlinear problems is introduced and illustrated with two examples. Techniques that are employed for model reduction include discretization, classification, and imposition of assignment constraints. The tradeoff between solution speed and optimality for the nonlinear problem is analyzed and demonstrated for the sample problem.&lt;/Abstract>
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