By Jayaraman Valadi, Patrick Siarry
Metaheuristics express fascinating homes like simplicity, effortless parallelizability and prepared applicability to kinds of optimization difficulties comparable to actual parameter optimization, combinatorial optimization and combined integer optimization. they're therefore commencing to play a key function in several industrially very important strategy engineering functions, between them the synthesis of warmth and mass trade apparatus, synthesis of distillation columns and static and dynamic optimization of chemical and bioreactors.
This ebook explains state of the art learn ideas in similar computational intelligence domain names and their functions in real-world approach engineering. will probably be of curiosity to business practitioners and examine academics.
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Extra resources for Applications of Metaheuristics in Process Engineering
Chem. Eng. 22(12), 1837–1850 (1998) 83. : A new heuristic optimization algorithm: Harmony search. Simulation 76(2), 60–68 (2001) 84. : Heuristics for integer programming using surrogate constraints. Decis. Sci. 8(1), 156–166 (1977) 85. : Future paths for integer programming and links to artificial intelligence. Comput. Oper. Res. 13(5), 533–549 (1986) 86. : Tabu Search. Kluwer Academic, Norwell (1997) 87. : Fundamentals of scatter search and path relinking. Control Cybern. 39(3), 653–684 (2000) 88.
22(10), 1387–1405 (1998) 136. : A generalized method for HEN synthesis using stochastic optimization I. General framework and MER optimal synthesis. Comput. Chem. Eng. 22(10), 1503–1513 (1998) 137. : Multi-objective particle swarm optimization hybrid algorithm: An application on industrial cracking furnace. Ind. Eng. Chem. Res. 46(11), 3602–3609 (2007) 138. : Kinetic parameters estimation in the polymerase chain reaction process using the genetic algorithm. Ind. Eng. Chem. Res. 51(40), 13,268– 13,273 (2012) 139.
MIT Press, Cambridge (1992) 125. : An evaluation of simulated annealing for batch process scheduling. Ind. Eng. Chem. Res. 30(1), 163–169 (1991) 126. : Vapor-liquid equilibrium of CO2 in aqueous solutions of 2-amino-2-methyl-1-propanol. J. Chem. Eng. Data 48(4), 789–796 (2003) 127. : Genetic algorithm optimisation of water consumption and wastewater network topology. J. Clean. Prod. 13(15), 1405–1415 (2005) 128. : Processes synthesis and design of distillation sequences using modular simulators: A genetic algorithm framework.