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

By Fei Tao, Lin Zhang, Yuanjun Laili

ISBN-10: 3319088394

ISBN-13: 9783319088396

ISBN-10: 3319088408

ISBN-13: 9783319088402

Presenting the concept that and layout and implementation of configurable clever optimization algorithms in production platforms, this e-book presents a brand new configuration approach to optimize production procedures. It presents a accomplished elaboration of easy clever optimization algorithms, and demonstrates how their development, hybridization and parallelization should be utilized to production. additionally, a number of purposes 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 normal complicated optimization mechanism that is hugely scalable with robustness and randomness. hence, this e-book demonstrates the pliability of those algorithms, in addition to their robustness and reusability as a way to remedy mass advanced difficulties in production.

Since the genetic set of rules used to be awarded a long time in the past, plenty 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 confirm their competence in fixing advanced difficulties in manufacturing.

This publication 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 novices, optimization engineers and senior set of rules designers. It deals an in depth description of clever optimization algorithms to set of rules novices; recommends new configurable layout equipment for optimization engineers, and offers destiny tendencies and demanding situations of the hot configuration mechanism to senior set of rules designers.

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Additional resources for Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing

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Therefore, the variables of combinatorial scheduling are generally integer. The targets are minimizing the task execution time and energy consumption in global or local workflow, and maximizing the quality (such as maintenance and reliability) and the efficiency of production or calculation. The constraints usually are the limits of resource capability, task size and other QoS indexes. The model is simple, while the solution space is typically huge. In addition, the variances and restrictions of variables are complex, which make the feasible solution space more narrow, so as to make the optimization harder.

Multi-disciplinary optimization is the least studied one in the problems above. Solution methods for it are mostly based on empirical adjustment and experimental simulation. Although most of the existing studies focus on the objects in manufacturing process, there are also some multi-disciplinary problems in the design and simulation of product structure, and system management and control. Now the methods of onside decision or multi-step optimization in collaborative manufacturing are inevitably not thorough enough.

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. Therefore, the variables to be solved usually include the parameters of control system and the critical sizes of part mechanical models.

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


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