By Lin Zhang, Fei Tao, Yuanjun Laili
Proposing the concept that and layout and implementation of configurable clever optimization algorithms in production structures, this ebook offers a brand new configuration option to optimize production techniques. It offers a complete elaboration of easy clever optimization algorithms, and demonstrates how their development, hybridization and parallelization may be utilized to production. moreover, numerous functions of those clever optimization algorithms are exemplified intimately, bankruptcy through bankruptcy. The clever optimization set of rules isn't just a unmarried set of rules; as a substitute it's a basic complicated optimization mechanism that's hugely scalable with robustness and randomness. for that reason, this booklet demonstrates the pliability of those algorithms, in addition to their robustness and reusability which will remedy mass advanced difficulties in manufacturing.
Since the genetic set of rules used to be offered a long time in the past, a good number of clever optimization algorithms and their advancements were constructed. in spite of the fact that, little paintings has been performed to increase their purposes and make certain their competence in fixing advanced difficulties in manufacturing.
This ebook will supply a useful source to scholars, researchers, experts and execs drawn to engineering optimization. it's going to even be fairly valuable to 3 teams of readers: set of rules rookies, 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 offers destiny developments and demanding situations of the hot configuration mechanism to senior set of rules designers.
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Extra resources for Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing (Springer Series in Advanced Manufacturing)
Because many constraints and objectives come from different fields and the relationships among these factors are complex, transformation and simplification are indispensable. On the other hand, simplification is 42 2 Recent Advances of Intelligent Optimization Algorithm in Manufacturing obtained based on the loss of modeling accuracy. The complexity of such problems is obviously huge. For example, in the control/mechanical collaborative optimization, not only the stability and the efficiency of the control system need to be guaranteed, but also the applicability and the portability of the mechanical model need to be improved.
The earliest studies of parallelization are mainly based on genetic algorithm. From then on, people have proposed many schemes for it. , master-slave parallel model, coarse-grained parallel model and fine-grained parallel model . These three frameworks made possible a variety of parallel intelligent optimization algorithms in recent decades, and the most typical examples are parallel genetic algorithms, parallel particle swarm optimizations and parallel ant colony optimizations. At present, studies on the parallelism of algorithms mainly focus on three aspects that can largely influence the parallel performance: parallel topology, communicational migration cycle, and the number of communicational migration.
Currently, many researchers have devoted to the function intellectualization of intelligent optimization algorithms, while the application intellectualization is rarely studied. For application, they tend to simply mix multiple operators, with the help of parameter adjustment and parallelism to adapt varying problems. However, ‘‘there is no free lunch’’ . H Wolpert’s theory had proven that enforcement of any algorithm to specific area in one aspect always needs additional cost in other aspects, not mention to a multi-suitable algorithm.