Global Optimization of Nonconvex Polynomial Programming Problems Having Rational Exponents
 Hanif D. Sherali
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This paper considers the solution of nonconvex polynomial programming problems that arise in various engineering design, network distribution, and locationallocation contexts. These problems generally have nonconvex polynomial objective functions and constraints, involving terms of mixedsign coefficients (as in signomial geometric programs) that have rational exponents on variables. For such problems, we develop an extension of the ReformulationLinearization Technique (RLT) to generate linear programming relaxations that are embedded within a branchandbound algorithm. Suitable branching or partitioning strategies are designed for which convergence to a global optimal solution is established. The procedure is illustrated using a numerical example, and several possible extensions and algorithmic enhancements are discussed.
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 Title
 Global Optimization of Nonconvex Polynomial Programming Problems Having Rational Exponents
 Journal

Journal of Global Optimization
Volume 12, Issue 3 , pp 267283
 Cover Date
 19980401
 DOI
 10.1023/A:1008249414776
 Print ISSN
 09255001
 Online ISSN
 15732916
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 Polynomial programs
 ReformulationLinearization Technique (RLT)
 Nonconvex programming
 Global optimization
 Industry Sectors
 Authors

 Hanif D. Sherali ^{(1)}
 Author Affiliations

 1. Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 240610118, U.S.A.