Lin Zhang, Fei Tao, Yuanjun Laili's Configurable Intelligent Optimization Algorithm: Design and PDF

By Lin Zhang, Fei Tao, Yuanjun Laili

ISBN-10: 3319088408

ISBN-13: 9783319088402

Featuring the concept that and layout and implementation of configurable clever optimization algorithms in production platforms, this publication offers a brand new configuration strategy to optimize production approaches. It offers a accomplished elaboration of simple clever optimization algorithms, and demonstrates how their development, hybridization and parallelization will be utilized to production. moreover, numerous purposes of those clever optimization algorithms are exemplified intimately, bankruptcy via bankruptcy. The clever optimization set of rules is not only a unmarried set of rules; in its place it's a basic complex optimization mechanism that's hugely scalable with robustness and randomness. accordingly, this booklet demonstrates the flexibleness of those algorithms, in addition to their robustness and reusability so as to remedy mass complex difficulties in manufacturing.

Since the genetic set of rules was once awarded a long time in the past, loads of clever optimization algorithms and their advancements were built. besides the fact that, little paintings has been performed to increase their functions and be certain their competence in fixing complex difficulties in manufacturing.

This booklet will supply a useful source to scholars, researchers, experts and pros drawn to engineering optimization. it is going to even be rather important to 3 teams of readers: set of rules rookies, optimization engineers and senior set of rules designers. It deals an in depth description of clever optimization algorithms to set of rules rookies; recommends new configurable layout tools for optimization engineers, and gives destiny traits and demanding situations of the recent configuration mechanism to senior set of rules designers.

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Additional resources for Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing (Springer Series in Advanced Manufacturing)

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With the above neighborhood search structures, many deterministic searching algorithms can be partly introduced into the iterative process to enhance the exploitation and find better solutions. It can also be designed as a bridge between traditional deterministic algorithms and the new advanced intelligent algorithms. 3 Review of Swarm Intelligence Algorithm Swarm intelligence algorithms search for optimal solution to the problem by individual collaboration and competition in population. The most representative ones are ant colony optimization and particle swarm optimization.

Though these neighborhood search methods were proposed relatively early, their ability for solving complex optimization problems is still strong. With the above neighborhood search structures, many deterministic searching algorithms can be partly introduced into the iterative process to enhance the exploitation and find better solutions. It can also be designed as a bridge between traditional deterministic algorithms and the new advanced intelligent algorithms. 3 Review of Swarm Intelligence Algorithm Swarm intelligence algorithms search for optimal solution to the problem by individual collaboration and competition in population.

It accounts for nearly half of optimization research. There are designs and applications for various kinds of certain and uncertain algorithms targeted to combinatorial scheduling, which covers every steps of manufacturing process and the management of manufacturing system. Then, in the next place, the numerical function optimization and the parameter optimization have a close number of studies. In numerical function optimization, the finite element analysis and structure optimization is the majority, and mainly target to the analysis of various kinds of product designs.

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Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing (Springer Series in Advanced Manufacturing) by Lin Zhang, Fei Tao, Yuanjun Laili


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