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Digital twin-driven dynamic scheduling for the assembly workshop of complex products with workers allocation

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2024年 89卷

作者： Gao, Qinglin Liu, Jianhua Li, Huiting Zhuang, Cunbo Liu, Ziwen Beijing Inst Technol Sch Mech Engn Lab Digital Mfg Beijing 100081 Peoples R China Beijing Inst Technol Tangshan Res Inst Tangshan 063015 Peoples R China Beijing Design Inst Electromech Engn Beijing 100039 Peoples R China

Assembly processes for complex products primarily involve manual assembly and often encounter various disruptive events, such as the insertion of new orders, order cancellations, task adjustments, workers absences, and job rotations. The dynamic scheduling problem for complex product assembly workshops requires consideration of trigger events and time nodes for rescheduling, as well as the allocations of multi-skilled and multilevel workers. The application of digital twin technology in smart manufacturing enables managers to more effectively monitor and control disruptive events and production factors on the production site. Therefore, a dynamic scheduling strategy based on digital twin technology is proposed to enable real-time monitoring of dynamic events in the assembly workshop, triggering rescheduling when necessary, adjusting task processing sequences and team composition accordingly, and establishing a corresponding dynamic scheduling integer programming model. Additionally, based on NSGA-II, an improved multi-objective evolutionary algorithm (IMOEA) is proposed, which utilizes the maximum completion time as the production efficiency indicator and the time deviation before and after rescheduling as the production stability indicator. Three new population initialization rules are designed, and the optimal parameter combination for these rules is determined. Finally, the effectiveness of the scheduling strategy is verified through the construction of a workshop digital twin system.

关键词： Dynamic scheduling Digital twin multi-objective evolutionary algorithm Hybrid flow shop Assembly workshop of complex products

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A system-of-systems meta-architecting approach for seru production system design

A system-of-systems meta-architecting approach for seru prod...

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IEEE International Conference on System of Systems Engineering (SoSE)

作者： Samuel Vanfossan Cihan H. Dagli Benjamin Kwasa Engineering Management and Systems Engineering Missouri University of Science and Technology Rolla USA

ISBN: (数字)9781728180502

ISBN: (纸本)9781728180519

Sponsored by expedient technologic innovation, consumers frequently expect manufacturer offerings to exhibit extensive product variety and regular product advancement. These expectations have rendered many traditional production practices less applicable. Chiefly impacted is the notion of mass produced, low-variety artifacts via massive assembly lines. These operations have difficulty meeting the high-customization, short life-cycle requirements imposed by contemporary demand. Many industries and organizations have begun the transformation from these rigid assembly mechanisms to a more versatile, cellular production strategy known as seru production. To facilitate this transition, methods are needed to aid manufacturers in appropriately selecting and arranging seru system components, a critical step in seru system design. Herein, a generalized model is proposed utilizing a system-of-systems architecting approach to determine the component assembly best suiting the needs of the manufacturing entity. Candidate architectures are generated and evaluated using a multi-objective genetic algorithm from which a preferred alternative is selected through a fuzzy inference system. Directing this genetic algorithm, domain-independent objectives are presented, maintaining applications to most seru production design scenarios. The proposed method is then applied to a camera production example, culminating in the identification of a well-performing architecture. The presented method should find increased use as organizations further adopt this flexible production methodology.

关键词： Seru production system meta-architecture generation multi-objective genetic algorithm fuzzy inference system system-of-systems architecting fuzzy inference system Product Design component assemble multi-objective evolutionary algorithm Assembly Lines Production systems

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Pareto efficient multi-objective test case selection 07

Pareto efficient multi-objective test case selection

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Proceedings of the 2007 international symposium on Software testing and analysis

作者： Shin Yoo Mark Harman King's College London

ISBN: (纸本)9781595937346

Previous work has treated test case selection as a single objective optimisation problem. This paper introduces the concept of Pareto efficiency to test case selection. The Pareto efficient approach takes multiple objectives such as code coverage, past fault-detection history and execution cost, and constructs a group of non-dominating, equivalently optimal test case subsets. The paper describes the potential bene?ts of Pareto efficient multi-objective test case selection, illustrating with empirical studies of two and three objective formulations.

关键词： multi-objective evolutionary algorithm test case selection

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Molecular Library Design Using multi-objective Optimization Methods

Molecular Library Design Using Multi-Objective Optimization ...

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作者： Christos A. Nicolaou Christos C. Kannas

Advancements in combinatorial chemistry and high-throughput screening technology have enabled the synthesis and screening of large molecular libraries for the purposes of drug discovery. Contrary to initial expectations, the increase in screening library size, typically combined with an emphasis on compound structural diversity, did not result in a comparable increase in the number of promising hits found. In an effort to improve the likelihood of discovering hits with greater optimization potential, more recent approaches attempt to incorporate additional knowledge to the library design process to effectively guide the search. multi-objective optimization methods capable of taking into account several chemical and biological criteria have been used to design collections of compounds satisfying simultaneously multiple pharmaceutically relevant objectives. In this chapter, we present our efforts to implement a multi-objective optimization method, MEGALib, custom-designed to the library design problem. The method exploits existing knowledge, e.g. from previous biological screening experiments, to identify and profile molecular fragments used subsequently to design compounds compromising the various objectives. less

关键词： High-throughput Screening Molecular Modeling multi-objective molecular library design multi-objective evolutionary algorithm selective library design MEGALib

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multi-objective design of UWB antennas using surrogate-based optimization

Multi-objective design of UWB antennas using surrogate-based...

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IEEE International Symposium on Antennas and Propagation

作者： S. Koziel S. Ogurtsov Eng. Optimization & Modeling Center Reykjavik Univ. Reykjavik Iceland

ISBN: (纸本)9781467353168

A procedure for multi-objective design of ultra-wideband (UWB) antennas is presented. The goal is to reduce the antenna size while ensuring that the matching requirements are satisfied. Our approach exploits the multi-objective evolutionary algorithm (MOEA) working with a fast surrogate model of the antenna obtained with kriging interpolation of coarse-discretization simulation data. Response correction techniques are subsequently applied to refine the designs obtained by MOEA. Our methodology allows us to obtain-at a low computational cost-a set of designs corresponding to various trade-offs between antenna size and matching.

关键词： Ultra wideband antennas ANTENNA Kriging interpolation multi-objective optimal design multi-objective evolutionary algorithm

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A Self-adaptation Framework for Dealing with the Complexities of Software Changes

A Self-adaptation Framework for Dealing with the Complexitie...

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2017 IEEE 8th International Conference on Software Engineering and Service Science

作者： Jiewen Wan Qingshan Li Lu Wang Liu He Yvjie Li Software Engineering Institute Xidian University

Software Self-adaption(SA) is a promising technology to reduce the cost of software maintenance. However, the complexities of software changes such as various and producing different effects, interrelated and occurring in an unpredictable context challenge the SA. The current methods may be insufficient to provide the required self-adaptation abilities to handle all the existent complexities of changes. Thus, this paper presents a self-adaptation framework which can provide a multi-agent system for self-adaptation control to equip software system with the required adaptation abilities. we employ the hybrid control mode and construct a two-layer MAPE control structure to deal with changes hierarchically. multiobjective evolutionary algorithm and Reinforcement Learning are applied to plan an adequate strategy for these changes. Finally, in order to validate the framework, we exemplify these ideas with a meta-Search system and confirm the required selfadaptive ability.

关键词： Self-adaptive systems Search-based software engineering multi-agent systems Reinforcement Learning multi-objective evolutionary algorithm

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A Filter Banks Design Using a multi-objective Genetic algorithm for Embedded Image Coding Scheme

A Filter Banks Design Using a Multi-objective Genetic Algori...

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International Symposium on Image and Signal Processing and Analysis

作者： A. Boukhobza A. Taleb Ahmed A. Bounoua N. Taleb RCAM Laboratory of research University of Sidi-Bel Abbes LAMIH Laboratory of research University of Valenciennes Valenciennes RCAM Laboratory of research University of Sidi-BelAbbes

ISBN: (纸本)9781424456499

A multi-objective genetic algorithm for the design of biorthogonal filter banks for embedded image coding application is presented. To be effective, the filter bank would satisfy multiple requirements related to such application. Flexibility in the design is introduced by imposing Near Perfect Reconstruction (N-PR) condition instead of entire PR condition as in conventional designs. Especially for embedded coding purposes, the filter banks are designed to be near-orthogonal. This can only be made possible by minimizing the deviation from the orthogonality in the optimization process. The optimization problem is formulated as a constrained multi-objective problem and solved using a constrained Non-dominated sorting genetic algorithm (C-NSGA) by searching solutions that achieve the best compromise between the different objective criteria, these solutions are known as Pareto Optimal Solutions. Experiment results show that our designed filter banks lead to improved performances of image coding compared to those achieved by the 9/7 filter bank of JPEG2000.

关键词： Filter banks embedded image coding Genetic algorithm (GA) Banks algorithm design JPEG image coding orthogonality Optimization Procedure multi-objective evolutionary algorithm

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The Pareto Optimization of Wide-Band Conformal Antenna Arrays

The Pareto Optimization of Wide-Band Conformal Antenna Array...

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2011 IEEE International Symposium on Antennas and Propagation(APSURSI 2011)

作者： Davide Bianchi Agostino Monorchio Simone Genovesi Alessandro Corucci Douglas H. Werner Ping L. Werner Dip. Ingegneria dell'Informazione University of Pisa Pisa Italy Dept. of Electrical Engineering The Pennsylvania State University University Park PA USA 16802

ISBN: (纸本)9781424495627;9781424495634

A design procedure for synthesizing wideband conformal antenna arrays based on a multi-objective evolutionary algorithm is presented. In this paper, raised power series (RPS) are employed as a simple yet effective way to introduce aperiodicity into a conformal semi-circular phased antenna array for achieving wideband performance. Unlike conventional linear array synthesis methods where, for example, the genetic algorithm (GA) has been utilized to meet a single design objective, the multi-objective optimization technique proposed in this paper employs the nondominated sorting GA version II (NSGA-II).

关键词： multi-objective optimization genetic algorithm (GA) Pareto wideband arrays conformal array raised power series Pareto optimisation conformal antennas design process multi-objective evolutionary algorithm design target Antenna arrays broadband antenna phased arrays Gallium

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Single-objective front optimization: application to rf circuit design 08

Single-objective front optimization: application to rf circu...

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Proceedings of the 10th annual conference on Genetic and evolutionary computation

作者： E. J. Solteiro Pires Luís Mendes P. B. de Moura Oliveira J. A. Tenreiro Machado N. M. Fonseca Ferreira João Vaz Maria Rosário UTAD University Vila Real Portugal Inst. Politécnico de Leiria Leiria Portugal Inst. Superior de Engenharia do Porto Porto Portugal Inst. Superior de Engenharia de Coimbra Coimbra Portugal Inst. Superior Técnico Lisboa Portugal

ISBN: (纸本)9781605581309

This paper proposes a new algorithm which promotes well distributed non-dominated fronts in the parameters space when a single-objective function is optimized. This lgorithm is based on µ-dominance concept and maxmin sorting scheme. Besides that, the paper also presents the results of the algorithm when it is used in the automated synthesis of optimum performance CMOS radio-frequency and microwave binary-weighted differential switched capacitor arrays (RFDSCAs). The genetic synthesis tool optimizes a fitness function which is based on the performance parameter of the RFDSCAs. To validate the proposed design methodology, a CMOS RFDSCA is synthesized, using a 0.25 ¼m BiCMOS technology.

关键词： multi-objective evolutionary algorithm single-objective front radio frequency circuit design

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A New Approach for Combining Yield and Performance in Behavioural Models for Analogue Integrated Circuits 08

A New Approach for Combining Yield and Performance in Behavi...

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2008 Design, Automation and Test in Europe (DATE 2008), vol.1

作者： Sawal Ali Reuben Wilcock Peter Wilson Andrew Brown University of Southampton UK

ISBN: (纸本)9783981080131

A new algorithm is presented that combines performance and variation objectives in a behavioural model for a given analogue circuit topology and process. The tradeoffs between performance and yield are analysed using a combination of a multi-objective evolutionary algorithm and Monte Carlo simulation. The results indicate a significant improvement in overall simulation time and efficiency compared to conventional simulation based approaches, without a corresponding drop in accuracy. This approach is particularly useful in the hierarchical design of large and complex circuits where computational overheads are often prohibitive. The behavioural model has been developed in Verilog-A and tested extensively with practical designs using the Spectre simulator. A benchmark OTA circuit was used to demonstrate the proposed algorithm and the behaviour has been verified with transistor level simulations of this circuit and a higher level filter design. This has demonstrated that an accurate performance and yield prediction can be achieved using this model, in a fraction of the time of conventional simulation based methods.

关键词： Analog integrated circuits Behavioural circuit complexity layer design multi-objective evolutionary algorithm simulating Monte Carlo technique behavioral models analog circuits

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