Thermal processing optimization through a modified adaptive random search

Journal of Food Engineering

Volumn 93, Issue 2, 2009, Pages 200-209

  Abakarov, A ^a   Sushkov, Yu ^b   Almonacid, S ^a   Simpson, R ^a  

^a DEPARTAMENTO DE FÍSICA   (Chile)

^b ST PETERSBURG STATE UNIVERSITY   (Russian Federation)

Author keywords

Global optimization; Logistic curve; Random search; Thermal processing

Indexed keywords

GLOBAL OPTIMIZATION; LOGISTICS; OPTIMIZATION; RAPID THERMAL ANNEALING;

ADAPTIVE RANDOM SEARCHES; FOOD INDUSTRIES; LOGISTIC CURVE; LOGISTIC FUNCTIONS; MULTI-MODAL OPTIMIZATIONS; OPTIMIZATION PROBLEMS; RANDOM SEARCH; THERMAL PROCESSING;

CURVE FITTING;

EID: 63149115852     PISSN: 02608774     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfoodeng.2009.01.013     Document Type: Article

References (49)

1. Abakarov A., and Sushkov Yu. The Statistical Research of Random Search. Mathematical models. Theory and Application (2002), Saint-Petersburg State University, Saint-Petersburg pp. 70-101
2. Abakarov, A., Sushkov, Y., 2005. The algorithm of adaptive random search for discrete-continuous optimization. In: Proceedings of the 5th St. Petersburg Workshop on Simulation, June 26-July 2, 2005, St. Petersburg State University, St. Petersburg, pp. 11-17.
3. Ali M., and Törn A. Population set based global optimization algorithms: some modifications and numerical studies. Comput. Oper. Res. 31 (2004) 1703-1725
4. Andersson J.A. Survey of Multiobjective Optimisation in Engineering Design, Reports of the Department of Mechanical Engineering, LiTH-IKP-R-1097 (2000), Linköping University, LinköSping
5. Banga, J.R. Casares, J.J., 1987. ICRS: application to a wastewater treatment plant model. In: The Institution of Chemical Engineers (Ed.), Process Optimisation (IChemE Symposium Series No. 100). Pergamon Press, Oxford (UK), pp. 183-192.
6. Banga J.R., Perez-Martin R.I., Gallardo J.M., and Casares J.J. Optimization of thermal processing of conduction-heated canned foods: study of several objective functions. Journal of Food Engineering 14 (1991) 25-51
7. Banga J.R., and Seider W.D. Global optimization of chemical processes using stochastic algorithms. In: Floudas C.A., and Pardalos P.M. (Eds). State of the Art in Global Optimization: Computational Methods and Applications (1996), Kluwer Academic Publishers, Dordrecht, The Netherlands 563-583
8. Banga J.R., Balsa-Canto E., Moles C.G., and Alonso A.A. Improving food processing using modern optimization methods. Trends in Food Science and Technology 14 4 (2003) 131-144
9. Banga J., Balsa-Canto E., Moles C.G., and Alonso A.A. Dynamic optimization of bioprocesses: efficient and robust numerical strategies. Journal of Biotechnology 117 4 (2005) 407-419
10. Chapman R.N. Animal Ecology (1931), McGraw-Hill, New York
11. Chen C.R., and Ramaswamy H.S. Modeling and optimization of variable retort temperature (VRT) thermal processing using coupled neural networks and genetic algorithms. Journal of Food Engineering 53 3 (2002) 209-220
12. Devaney M. A First Course in Chaotic Dynamical Systems (1992), Westview Press
13. Dorigo M. Optimization, Learning and Natural Algorithms (1992), Ph.D. thesis, Dipartimento di Elettronica, Politecnico di Milano, Italy in Italian
14. Dorigo M., and Gambardella L.M. Ant Colony System: a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1 1 (1997) 53-66
15. Dorigo M., and Stu{combining double acute accent}tzle T. Ant Colony Optimization (2004), MIT Press, Cambridge, MA
16. García M.S.G., Balsa-Canto E., Alonso A.A., and Banga J.R. Computing optimal operating policies for the food industry. Journal of Food Engineering 74 1 (2005) 13-23
17. Glover F. Tabu search - part I. ORSA Journal on Computing 1 (1989) 190-206
18. Gordon F. Logistic population growth in the world's largest cities. Geographical Analysis 38 4 (2006) 344-370
19. Himmelblau D.M. Applied Nonlinear Programming (1972), McGraw-Hill Book Company, New York
20. Holdsworth S.D., and Simpson R. Thermal processing of packaged foods. 2nd edition. (2007), Springer, New York, USA p. 412
21. Holland H.J. Adaptation in Natural and Artificial Systems, An Introductory Analysis with Application to Biology Control and Artificial Intelligence (1975), The University of Michigan Press, Ann Arbor
22. Horst, R., Pardalos, P.M. (Eds.), 1995. Handbook of Global Optimization. Dordrecht etc. Kluwer Academic Publishers, p. 880 (XVII).
23. Hosmer D.W., and Lemeshow S. Applied Logistic Regression (2000), Wiley, New York
24. Kirkpatrick S., Gelatt C.D., and Vecchi Jr. M.P. Optimization by simulated annealing. Science 220 4598 (1983) 671-680
25. Krose B.J.A. In: Patrick van der Smagt P. (Ed). An Introduction to Networks Neural. fifth ed. (1993), The University of Amsterdam
26. Li B., and Jiang W.S. Optimizing complex function by chaos search. Cybern Syst. 29 4 (1998) 409-419
27. Marin O., and Buckius R.O. A model of the cumulative distribution function for wide band radiative properties. JQSRT 59 (1998) 671-685
28. May R. Simple mathematical models with very complicated dynamics. Nature 261 (1976) 459-467
29. Moate P., Dougherty L., Schnall M., Landis R., and Boston R. A modified logistic model to describe gadolinium kinetics in breast tumors. Magnetic Resonance Imaging 22 (2004) 467-473
30. Molles M.C. Ecology: Concepts and Applications. third ed. (2004), McGraw-Hill, New York pp. 280-286, 347-371
31. Neelesh K., Jain V., and Deb K. Optimization of process parameters of mechanical type advanced machining processes using genetic algorithms. International Journal of Machine Tools and Manufacture 47 (2007) 900-919
32. Price W.L. A controlled random search procedure for global optimization. Comput. J. 20 (1977) 367-370
33. Rastrigin, L.A., Rubinstein, Y., 1996. Theory and Application of Random Search. Riga, Zinatne, p. 305.
34. Rechenberg, I., 1973. Evolutionsstrategie - Optimierung Technischer Systeme nach Prinzipien der Biologischen Evolution. Friedrich Frommann Verlag.
35. Schlegel M., Stockmann K., Binder T., and Marquardt W. Dynamic optimization using adaptive control vector parameterization. Comp. Chem. Eng. 29 (2005) 1731-1751
36. Simpson R., Almonacid S., and Teixeira A. Optimization criteria for batch retort battery design and operation in food canning-plants. Journal of Food Process Engineering 25 6 (2003) 515-538
37. Simpson R., Abakarov A., and Teixeira A. Variable retort temperature optimization using adaptive random search techniques. Journal of Food Control 19 11 (2008) 1023-1032
38. Socha K., and Dorigo M. Ant colony optimization for continuous domains. European Journal of Operational Research 185 (2008) 1155-1173
39. Sushkov Yu, A., 1969. Method, Algorithm and Program of Random Search. Leningrad, VNII Transmash, p. 43.
40. Teixeira A.A., Dixon J.R., Zahradnik J.W., and Zinsmeister G.E. Computer optimization of nutrient retention in thermal processing of conduction-heated foods. Food Technology 23 6 (1969) 137-142
41. Teixeria A.A., Zinsmeister G.E., and Zahradnik J.W. Computer simulation of variable retort control and container geometry as a possible means of improving thiamine retention in thermally-processed foods. Journal of Food Science 40 3 (1975) 656-659
42. Teixeira A.A. Thermal process calculations. In: Heldman D.R., and Lund D.B. (Eds). Handbook of food engineering (1992), Marcel Dekker Inc., New York 563-619
43. Tikhomirov A., Stojunina T., and Nekrutkin V. Monotonous random search on a torus: integral upper bounds for the complexity. Journal of Statistical Planning and Inference 137 (2007) 4031-4047
44. Tvrdík J., Křivý I., and Mišík L. Adaptive population-based search: application to estimation of nonlinear regression parameters. Computational Statistics and Data Analysis 52 (2007) 713-724
45. Verhulst P.-F. Recherches mathématiques sur la loi d'accroissement de la population. Nouv. mém. de l'Academie Royale des Sci. Et Belles-Lettres de Bruxelles 18 (1845) 1-41
46. Dixiong Yang, Gang Li, Gengdong Cheng, 2007. On the efficiency of chaos optimization algorithms for global optimization. Chaos, Solitons and Fractals 34, 1366-1375.
47. Yua Z., and Pu D. A new nonmonotone line search technique for unconstrained optimization. Journal of Computational and Applied Mathematics 219 (2008) 134-144
48. Zhigljavsky A.A. Theory of Global Random Search (1991), Kluwer Academic Publishers, Dordrecht
49. Zhigljavsky, A., Zilinskas, A.G., 2008. Stochastic Global Optimization. Ser. Springer Optimization and Its Applications, vol. 9. Springer-Verlag, Berlin, xvi+362 p. ISBN:0-387-36720-0.