The convex hull heuristic for nonlinear integer programming problems with linear constraints and application to quadratic 0–1 problems

Author:

Guignard MoniqueORCID,Ahlatcioglu AykutORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Management Science and Operations Research,Control and Optimization,Computer Networks and Communications,Information Systems,Software

Reference25 articles.

1. Ahlatcioglu, A., Guignard, M.: The convex hull relaxation for nonlinear integer programs with linear constraints. Technical report, University of Pennsylvania, The Wharton School, OPIM Department, Philadelphia, PA (2007–2009)

2. Ahlatcioglu, A., Bussieck, M., Esen, M., Guignard, M., Jagla, J.-H., Meeraus, A.: Combining QCR and CHR for convex quadratic pure 0–1 programming problems with linear constraints. Ann. Oper. Res. 199, 33–49 (2012)

3. Ahn, S.: On solving some optimization problems in stochastic and integer programming with applications in finance and banking. Ph.D. dissertation, University of Pennsylvania (1997)

4. Albornoz, V.: Diseno de Modelos y Algoritmos de Optimizacion Robusta y su Aplicacion a la Planicacion Agregada de la Produccion. Ph.D. thesis, Universidad Catolica de Chile, Santiago, Chile (1998)

5. Anstreicher, K.M., Brixius, N.W.: Solving quadratic assignment problems using convex quadratic programming relaxations. Optim. Methods Softw. 16, 49–68 (2001)

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