Configurable Intelligent Optimization Algorithm: Design and by Lin Zhang, Fei Tao, Yuanjun Laili

By Lin Zhang, Fei Tao, Yuanjun Laili

Proposing the idea that and layout and implementation of configurable clever optimization algorithms in production structures, this booklet presents a brand new configuration solution to optimize production methods. It presents a finished elaboration of easy clever optimization algorithms, and demonstrates how their development, hybridization and parallelization could be utilized to production. in addition, numerous functions of those clever optimization algorithms are exemplified intimately, bankruptcy by way of bankruptcy. The clever optimization set of rules is not only a unmarried set of rules; as a substitute it's a basic complex optimization mechanism that's hugely scalable with robustness and randomness. consequently, this publication demonstrates the pliability of those algorithms, in addition to their robustness and reusability as a way to clear up mass advanced difficulties in manufacturing.

Since the genetic set of rules was once provided many years in the past, a lot of clever optimization algorithms and their advancements were constructed. despite the fact that, little paintings has been performed to increase their purposes and determine their competence in fixing advanced difficulties in manufacturing.

This booklet will offer a useful source to scholars, researchers, experts and pros drawn to engineering optimization. it is going to even be quite necessary to 3 teams of readers: set of rules newbies, optimization engineers and senior set of rules designers. It deals a close description of clever optimization algorithms to set of rules novices; recommends new configurable layout tools for optimization engineers, and gives destiny tendencies and demanding situations of the hot configuration mechanism to senior set of rules designers.

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

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Besides, in their respective fields, researchers have successfully developed various forms of decision-making system based on typical intelligent optimization algorithms such as the genetic algorithm and ant colony algorithm, and have brought much efficiency to field decision-making. From the perspective of optimization algorithm development and application, in studies based on most specific problems, most researchers tend to re-design algorithms or directly use one or several traditional algorithms and improvement strategies according to problem features.

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