Constrained Global Optimization: Algorithms and Applications - Pardalos, Panos M.; Rosen, J. Ben
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Global optimization is concerned with the characterization and computation of global minima or maxima of nonlinear functions. Such problems are widespread in mathematical modeling of real world systems for a very broad range of applications. The applications include economies of scale, fixed charges, allocation and location problems, quadratic assignment and a number of other combinatorial optimization problems. More recently it has been shown that certain aspects of VLSI chip design and database problems can be formulated as constrained global optimization problems with a quadratic objective…mehr

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Produktbeschreibung
Global optimization is concerned with the characterization and computation of global minima or maxima of nonlinear functions. Such problems are widespread in mathematical modeling of real world systems for a very broad range of applications. The applications include economies of scale, fixed charges, allocation and location problems, quadratic assignment and a number of other combinatorial optimization problems. More recently it has been shown that certain aspects of VLSI chip design and database problems can be formulated as constrained global optimization problems with a quadratic objective function. Although standard nonlinear programming algorithms will usually obtain a local minimum to the problem , such a local minimum will only be global when certain conditions are satisfied (such as f and K being convex).
Autorenporträt
Xiucui Guan obtained her Ph.D. at City University of Hong Kong on 2005 majoring in combinatorial optimization. After graduation, she worked as a lecturer from May 2005 to April 2007 and an associate professor from May 2007 to April 2018 at School of Mathematics, Southeast University, China. She has been employed as a professor of School of Mathematics since May 2018. I had visited Prof. Panos M. Pardalos at Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Florida for one year since February 2013. Her research interest includes discrete optimization, inverse combinatorial optimization, linear programming, algorithm design and analysis, etc. She has published more than 40 papers on combinatorial optimization, including more than 20 SCI indexed papers. I have been supported by 6 projects and 3 of them were supported by National Natural Science Foundation of China. I have cultivated 17 graduate students to obtain their masters’ degree at Mathematics and 3 Ph.D. students. I mainly study on Inverse Combinatorial Optimization Problems (ICOP) including inverse linear programming problems, inverse minimum/max+sum spanning tree problems, inverse center/median location problems, shortest path improvement/interdiction problems, etc. We built mathematical models for these ICOPs, analyzed their properties and designed efficient algorithms to solve them. There are many applications of ICOPs in the field of transportation networks, communication networks, geophysical sciences, electricity markets, medical decision-making areas, etc. Researches on the ICOPs can help solve their corresponding problems in applications.