Recent Advances in Computational Optimization
Fidanova, Stefka (EDT)
Sold by GreatBookPrices, Columbia, MD, U.S.A.
AbeBooks Seller since April 6, 2009
New - Soft cover
Condition: New
Quantity: 15 available
Add to basketSold by GreatBookPrices, Columbia, MD, U.S.A.
AbeBooks Seller since April 6, 2009
Condition: New
Quantity: 15 available
Add to basketOptimization is part of our everyday life. We try to organize our work in a better way and optimization occurs in minimizing time and cost or the maximization of the profit, quality and efficiency.
Also many real world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks.
This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization.
This book presents recent advances in computational optimization. The volume includes important real world problems like parameter settings for con- trolling processes in bioreactor, robot skin wiring, strip packing, project scheduling, tuning of PID controller and so on. Some of them can be solved by applying traditional numerical methods, but others need a huge amount of computational resources. For them it is shown that is appropriate to develop algorithms based on metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming etc.
Optimization is part of our everyday life. We try to organize our work in a better way and optimization occurs in minimizing time and cost or the maximization of the profit, quality and efficiency.
Also many real world problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks.
This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization.
This book presents recent advances in computational optimization. The volume includes important real world problems like parameter settings for con- trolling processes in bioreactor, robot skin wiring, strip packing, project scheduling, tuning of PID controller and so on. Some of them can be solved by applying traditional numerical methods, but others need a huge amount of computational resources. For them it is shown that is appropriate to develop algorithms based on metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming etc.
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