Multidisciplinary collaborative optimization based on relaxation method for solving complex problems

Chagraoui, Hamda; Soula, Mohamed

doi:10.1177/1063293x20958921

Cited by 4 publications

(4 citation statements)

References 25 publications

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“…Typical single-level optimization methods include multiple discipline feasible method, individual discipline feasible method and all-at-once method. Multi-level optimization methods include concurrent subspace optimization method (CSSO) [28,29], collaborative optimization method (CO) [30][31][32], bi-level integrated system synthesis (BLISS) [33] and analytical target Cascading method (ATC) [34]. The disciplines such as orbit, payload, power and quality that mentioned in this paper have complex coupling relationships, which belong to a non-hierarchical system.…”

Section: The Main Content Of Mbse-mdomentioning

confidence: 99%

Multidisciplinary Modeling and Optimization Method of Remote Sensing Satellite Parameters Based on SysML-CEA

Chu¹,

Yin²,

Shi³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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To enhance the efficiency of system modeling and optimization in the conceptual design stage of satellite parameters, a system modeling and optimization method based on System Modeling Language and Co-evolutionary Algorithm is proposed. At first, the objectives of satellite mission and optimization problems are clarified, and a design matrix of discipline structure is constructed to process the coupling relationship of design variables and constraints of the orbit, payload, power and quality disciplines. In order to solve the problem of increasing nonlinearity and coupling between these disciplines while using a standard collaborative optimization algorithm, an improved genetic algorithm is proposed and applied to system-level and discipline-level models. Finally, the CO model of satellite parameters is solved through the collaborative simulation of Cameo Systems Modeler (CSM) and MATLAB. The result obtained shows that the method proposed in this paper for the conceptual design phase of satellite parameters is efficient and feasible. It can shorten the project cycle effectively and additionally provide a reference for the optimal design of other complex projects.

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Section: The Main Content Of Mbse-mdomentioning

confidence: 99%

Multidisciplinary Modeling and Optimization Method of Remote Sensing Satellite Parameters Based on SysML-CEA

Chu¹,

Yin²,

Shi³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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“…However, it still has some limitations, such as instability of convergence and decreased efficiency when there are more coupling variables [37]. To overcome these difficulties, many improved CO methods, including enhanced collaborative optimization (ECO) and modified collaborative optimization (MCO), have been proposed and applied to MDO [38][39][40][41].…”

Section: Classification Of Mdo Architecturesmentioning

confidence: 99%

A Review of Uncertainty-Based Multidisciplinary Design Optimization Methods Based on Intelligent Strategies

Wang,

Fan,

Qiang

2023

Symmetry

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The design of aerospace systems is recognized as a complex interdisciplinary process. Many studies have shown that the exchange of information among multiple disciplines often results in strong coupling and nonlinearity characteristics in system optimization. Meanwhile, inevitable multi-source uncertainty factors continuously accumulate during the optimization process, greatly compromising the system’s robustness and reliability. In this context, uncertainty-based multidisciplinary design optimization (UMDO) has emerged and has been preliminarily applied in aerospace practices. However, it still encounters major challenges, including the complexity of multidisciplinary analysis modeling, and organizational and computational complexities of uncertainty analysis and optimization. Extensive research has been conducted recently to address these issues, particularly uncertainty analysis and artificial intelligence strategies. The former further enriches the UMDO technique, while the latter makes outstanding contributions to addressing the computational complexity of UMDO. With the aim of providing an overview of currently available methods, this paper summarizes existing state-of-the art UMDO technologies, with a special focus on relevant intelligent optimization strategies.

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“…Farmani et al integrated the multi-objective particle swarm optimization into the collaborative optimization to provide an efficient framework for design and analysis of multidisciplinary design optimization [7] . Chagraoui et al proposed a new relaxation method to solve the difficult convergence and low accuracy problem [8] . Therefore, it is essential to combine heuristic algorithms with CO algorithm to overcome the difficulty of convergence given the existing of highly nonlinear consistency constraints.…”

Section: Introductionmentioning

confidence: 99%

Multidisciplinary collaborative optimization for product design based on dual-loop wolf pack algorithm

Zhao

Zhao²,

Zhao³

2022

International Conference on Intelligent Manufacturing and Industrial Automation (CIMIA 2022)

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Complex product design generally involves multiple subdisciplines or subsystems. In this study, taking the two-stage planetary gear transmission system as an example, a multi-objective optimization model for multidisciplinary design is established and solved by collaborative optimization method. The goal of the optimization is to simultaneously minimize volume and maximize efficiency. In the model, the sequential quadratic programming (SQP) method is used for individual disciplinary optimization, and an improved wolf pack algorithm is developed as the optimizer at system level for the CO method. It is shown that the proposed method can realize the requirement of miniaturization of the part while ensuring the transmission efficiency almost undamaged, and obtains accurate and efficient optimization results.

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Multidisciplinary collaborative optimization based on relaxation method for solving complex problems

Cited by 4 publications

References 25 publications

Multidisciplinary Modeling and Optimization Method of Remote Sensing Satellite Parameters Based on SysML-CEA

Multidisciplinary Modeling and Optimization Method of Remote Sensing Satellite Parameters Based on SysML-CEA

A Review of Uncertainty-Based Multidisciplinary Design Optimization Methods Based on Intelligent Strategies

Multidisciplinary collaborative optimization for product design based on dual-loop wolf pack algorithm

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