Ivorra, BenjaminRamos del Olmo, Ángel ManuelMohammadi, B.2023-06-202023-06-202007Mohammadi, B., Saiac, J.H.: Pratique de la Simulation Numérique. Dunod, Paris (2002) Attouch, H., Cominetti, R.: A dynamical approach to convex minimization coupling approximation with the steepest descent method. J. Differ. Equ. 128(2), 519–540 (1996)Shivamoggi, B.K.: Theoretical Fluid Dynamics. Martinus Nijhoff Publishers, Dordrecht (1985) Goldberg, D.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison–Wesley,Reading (1989) Dumas, L., Herbert, V., Muyl, F.: Hybrid method for aerodynamic shape optimization in automotive industry. Comput. Fluids 33(5), 849–858 (2004) Liu, D.C., Nocedal, J.: On the limited memory BFGS method for large-scale optimization. Math.Program. 45, 503–528 (1989) Ivorra, B. Semi-deterministic global optimization. PhD Thesis, Montpellier University, France (2006) Debiane, L., Ivorra, B., Mohammadi, B., Nicoud, F., Ern, A., Poinsot, T., Pitsch, H.: A low-complexity global optimization algorithm for temperature and pollution control in flames with complex chemistry.Int. J. Comput. Fluid Dyn. 20(2), 93–98 (2006) Ivorra, B., Mohammadi, B., Santiago, J.G., Hertzog, D.E.:Semi-deterministic and genetic algorithms for global optimization of microfluidic protein folding devices. Int.J. Numer. Methods Eng. 66(2),319–333 (2006) Ivorra, B., Mohammadi, B., Redont, P., Dumas, L., Durand, O.: Semi-deterministic vs. genetic algorithms for global optimization of multichannel optical filters. Int. J.Comput. Sci. Eng. 2(3), 170–178 (2006) Broyden, C.G., Fletcher, R., Goldfarb, D., Shanno, D.F.:BFGS method. J. Inst. Math. Appl. 6, 76–90 (1970) Ramos, A.M., Glowinski, R., Periaux, J.: Pointwise control of the Burgers equation and related Nash equilibrium problems: computational approach. J. Optim. Theory Appl. 112(3), 499–516 (2002)0022-323910.1007/s10957-007-9251-8https://hdl.handle.net/20.500.14352/50288This paper has two objectives. We introduce a new global optimization algorithm reformulating optimization problems in terms of boundary-value problems. Then, we apply this algorithm to a pointwise control problem of the viscous Burgers equation, where the control weight coefficient is progressively decreased. The results are compared with those obtained with a genetic algorithm and an LM-BFGS algorithm in order to check the efficiency of our method and the necessity of using global optimization techniques.engjournal articlehttp://www.springerlink.com/content/4243535816624737/fulltext.pdfhttp://www.springerlink.comrestricted access519.8Global optimizationSemideterministic algorithmGenetic algorithmOptimal control problemBurgers equationInvestigación operativa (Matemáticas)1207 Investigación Operativa