scholarly journals Evaluation of Cloud 3D Printing Order Task Execution Based on the AHP-TOPSIS Optimal Set Algorithm and the Baldwin Effect

Micromachines ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 801
Author(s):  
Chenglei Zhang ◽  
Cunshan Zhang ◽  
Jiaojiao Zhuang ◽  
Hu Han ◽  
Bo Yuan ◽  
...  
Keyword(s):  
3D Printing ◽  
Evaluation Framework ◽  
Pareto Optimal ◽  
Task Execution ◽  
Baldwin Effect ◽  
Pareto Optimal Set ◽  
Order Task ◽  
Manufacturing Environments ◽  
The Baldwin Effect ◽  
Optimal Set

Focusing on service control factors, rapid changes in manufacturing environments, the difficulty of resource allocation evaluation, resource optimization for 3D printing services (3DPSs) in cloud manufacturing environments, and so on, an indicator evaluation framework is proposed for the cloud 3D printing (C3DP) order task execution process based on a Pareto optimal set algorithm that is optimized and evaluated for remotely distributed 3D printing equipment resources. Combined with the multi-objective method of data normalization, an optimization model for C3DP order execution based on the Pareto optimal set algorithm is constructed with these agents’ dynamic autonomy and distributed processing. This model can perform functions such as automatic matching and optimization of candidate services, and it is dynamic and reliable in the C3DP order task execution process based on the Pareto optimal set algorithm. Finally, a case study is designed to test the applicability and effectiveness of the C3DP order task execution process based on the analytic hierarchy process and technique for order of preference by similarity to ideal solution (AHP-TOPSIS) optimal set algorithm and the Baldwin effect.

scholarly journals Evaluation of Cloud 3D Printing Order Task Execution Based on the AHP-TOPSIS Optimal Set Algorithm and The Baldwin Effect

2021 ◽  
Author(s):  
Chenglei ZHANG ◽  
Cunshan ZHANG ◽  
Jiaojiao ZHUANG ◽  
Hu HAN ◽  
Bo YUAN ◽  
...  
Keyword(s):  
3D Printing ◽  
Evaluation Framework ◽  
Pareto Optimal ◽  
Task Execution ◽  
Baldwin Effect ◽  
Pareto Optimal Set ◽  
Order Task ◽  
Manufacturing Environments ◽  
The Baldwin Effect ◽  
Optimal Set

Focusing on service control factors, rapid changes in manufacturing environments, the difficulty of resource allocation evaluation, resource optimization for 3D printing services (3DPSs) in cloud manufacturing environments and so on, an indicator evaluation framework is proposed for the cloud 3D printing (C3DP) order task execution process based on a Pareto optimal set algorithm that is optimized and evaluated for remotely distributed 3D printing equipment resources. Combined with the multi-objective method of data normalization, an optimization model for C3DP order execution based on the Pareto optimal set algorithm is constructed with these agents' dynamic autonomy and distributed processing. This model can perform functions such as automatic matching and optimization of candidate services, and it is dynamic and reliable in the C3DP order task execution process based on the Pareto optimal set algorithm. Finally, a case study is designed to test the applicability and effectiveness of the C3DP order task execution process based on the analytic hierarchy process and technique for order of preference by similarity to ideal solution (AHP-TOPSIS) optimal set algorithm and the Baldwin effect.

Analytical Derivation of the Pareto-Optimal Set with Application to Structural Design

2020 ◽  
pp. 43-66
Author(s):  
Federico Maria Ballo ◽  
Massimiliano Gobbi ◽  
Giampiero Mastinu ◽  
Giorgio Previati
Keyword(s):  
Structural Design ◽  
Pareto Optimal ◽  
Analytical Derivation ◽  
Pareto Optimal Set ◽  
Optimal Set

Optimal Approximation of Real Values Using Rational Numbers With Application to the Kinematic Design of Gearboxes

1993 ◽  
Author(s):  
Leonard P. Pomrehn ◽  
Panos Y. Papalambros
Keyword(s):  
Design Problem ◽  
Rational Numbers ◽  
Optimal Approximation ◽  
Pareto Optimal ◽  
Individual Stage ◽  
Gear Teeth ◽  
Kinematic Design ◽  
Pareto Optimal Set ◽  
Reducing Gear ◽  
Optimal Set

Abstract This article proposes a method for optimally approximating real values with rational numbers. Such requirements arise in the design of various types of gear sets, where integer numbers of gear teeth force individual stage ratios to assume rational values. The kinematic design of an 18-speed gearbox, taken from the literature, is analyzed and solved using the proposed method. The method, called sequential exhaustion, sequentially considers each stage of the gearbox design, exhaustively examining each stage. Examination of 94 solutions leads to a pareto-optimal set containing 11 solutions. Further, although the layout of the gearbox is predefined for the kinematic design problem, certain solutions of the problem exhibit “non-reducing” gear pairs, revealing previously unforeseen changes in the gearbox layout.

The Skewboid Method: A Simple and Effective Approach to Pareto Relaxation and Filtering

2012 ◽  
Author(s):  
Matthew I. Campbell
Keyword(s):  
Pareto Optimality ◽  
Population Based ◽  
Pareto Optimal ◽  
Large Set ◽  
Number Of Solutions ◽  
Target Number ◽  
Relaxation Methods ◽  
Pareto Optimal Set ◽  
Optimal Set ◽  
Adjustment Parameter

The concept of Pareto optimality is the default method for pruning a large set of candidate solutions in a multi-objective problem to a manageable, balanced, and rational set of solutions. While the Pareto optimality approach is simple and sound, it may select too many or too few solutions for the decision-maker’s needs or the needs of optimization process (e.g. the number of survivors selected in a population-based optimization). This inability to achieve a target number of solutions to keep has caused a number of researchers to devise methods to either remove some of the non-dominated solutions via Pareto filtering or to retain some dominated solutions via Pareto relaxation. Both filtering and relaxation methods tend to introduce many new adjustment parameters that a decision-maker (DM) must specify. In the presented Skewboid method, only a single parameter is defined for both relaxing the Pareto optimality condition (values between −1 and 0) and filtering more solutions from the Pareto optimal set (values between 0 and 1). This parameter can be correlated with a desired number of solutions so that this number of solutions is input instead of an unintuitive adjustment parameter. A mathematically sound derivation of the Skewboid method is presented followed by illustrative examples of its use. The paper concludes with a discussion of the method in comparison to similar methods in the literature.

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