The lithography process in semiconductor dynamic random-access memory (DRAM) fabrication plants (fabs) is usually a major bottleneck, and reticle scheduling is complicated by process-specific constr...
{"title":"Lithography reticle scheduling in semiconductor manufacturing","authors":"Chia-Yen Lee, Cheng-Man Wu, Chia-Yi Hsu, Hui-Hua Xie, Yu-Hsueh Fang","doi":"10.1080/0305215x.2023.2285416","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2285416","url":null,"abstract":"The lithography process in semiconductor dynamic random-access memory (DRAM) fabrication plants (fabs) is usually a major bottleneck, and reticle scheduling is complicated by process-specific constr...","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"9 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138542317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-27DOI: 10.1080/0305215x.2023.2283603
Xiaoju Zhang, Yue Gu, Yuan Tian
To improve the operational efficiency of automated container terminals and the coordination between multiple operations, this article studies the integrated scheduling optimization problem of autom...
{"title":"Integrated optimization of automated guided vehicles and yard cranes considering charging constraints","authors":"Xiaoju Zhang, Yue Gu, Yuan Tian","doi":"10.1080/0305215x.2023.2283603","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2283603","url":null,"abstract":"To improve the operational efficiency of automated container terminals and the coordination between multiple operations, this article studies the integrated scheduling optimization problem of autom...","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"87 7","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138525618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AbstractThe bin packing problem is a classical problem widely existing in practical applications, such as shipping, warehousing and manufacturing industries. Whereas current research mainly focuses on reducing packing costs by optimizing the packing scheme, this study explores a novel approach by redesigning the bin sizes to fit the items ready to be packed. Specifically, this study considers a general three-dimensional open dimension problem (3D-ODP) where all dimensions, i.e. length, width and height, of a number of heterogeneous bin types are unknown and need to be decided. Based on the designed bin types, the corresponding packing scheme with minimal total costs is optimized, which is referred to as a three-dimensional multiple-bin-size bin packing problem (3D-MBSBPP). The combination of 3D-ODP and 3D-MBSBPP is redefined as a three-dimensional bin design and packing problem (3D-BDPP), for which a two-layer heuristic is developed. It consists of an outer heuristic framework (i.e. genetic algorithm or differential evolution algorithm) to design bin types, and an inner deterministic constructive heuristic (i.e. placement algorithm) to generate an effective solution for the 3D-MBSBPP. Extensive simulation tests on the classical benchmark and a case study derived from an e-commerce company are conducted to verify the algorithms and deduce managerial insights.Keywords: Open dimension problemthree-dimensionalbin-packing problembin designtwo-layer heuristic Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe experimental data in Section 5.1 and the data of items in Section 5.2 are available from Alvarez-Valdes, Parreño, and Tamarit (Citation2013) with the permission of the authors. The data of bin sizes in Section 5.2 are available from the corresponding author upon request. The case study data in Section 5.3 are not available owing to commercial restrictions.Additional informationFundingThis work is supported by the National Natural Science Foundation of China [grant No. 71772100].
{"title":"Two-layer heuristic for the three-dimensional bin design and packing problem","authors":"Ying Yang, Zili Wu, Xiaodeng Hao, Huiqiang Liu, Mingyao Qi","doi":"10.1080/0305215x.2023.2269868","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2269868","url":null,"abstract":"AbstractThe bin packing problem is a classical problem widely existing in practical applications, such as shipping, warehousing and manufacturing industries. Whereas current research mainly focuses on reducing packing costs by optimizing the packing scheme, this study explores a novel approach by redesigning the bin sizes to fit the items ready to be packed. Specifically, this study considers a general three-dimensional open dimension problem (3D-ODP) where all dimensions, i.e. length, width and height, of a number of heterogeneous bin types are unknown and need to be decided. Based on the designed bin types, the corresponding packing scheme with minimal total costs is optimized, which is referred to as a three-dimensional multiple-bin-size bin packing problem (3D-MBSBPP). The combination of 3D-ODP and 3D-MBSBPP is redefined as a three-dimensional bin design and packing problem (3D-BDPP), for which a two-layer heuristic is developed. It consists of an outer heuristic framework (i.e. genetic algorithm or differential evolution algorithm) to design bin types, and an inner deterministic constructive heuristic (i.e. placement algorithm) to generate an effective solution for the 3D-MBSBPP. Extensive simulation tests on the classical benchmark and a case study derived from an e-commerce company are conducted to verify the algorithms and deduce managerial insights.Keywords: Open dimension problemthree-dimensionalbin-packing problembin designtwo-layer heuristic Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe experimental data in Section 5.1 and the data of items in Section 5.2 are available from Alvarez-Valdes, Parreño, and Tamarit (Citation2013) with the permission of the authors. The data of bin sizes in Section 5.2 are available from the corresponding author upon request. The case study data in Section 5.3 are not available owing to commercial restrictions.Additional informationFundingThis work is supported by the National Natural Science Foundation of China [grant No. 71772100].","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"137 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136352096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-13DOI: 10.1080/0305215x.2023.2269849
Dongjun Cai, Xi Xiang, Loo Hay Lee, Ek Peng Chew, Kok Choon Tan
AbstractA robotic compact storage and retrieval system (RCSRS) is a grid-based system that has been popularly implemented by online retailers around the world recently. This article addresses a robot dispatching problem for RCSRS, aiming to reduce robot empty travelling time and workstation idle time. The robot dispatching problem is to assign tasks to robots when the task sequences in workstations are given. Additionally, the robots follow a fast dual-command transaction process in this problem. Hence, a mixed integer programming model catering for the dual-command transaction process is formulated to optimize system performance. Furthermore, an adaptive neighbourhood search with an ε-greedy algorithm is proposed to solve the problem. The experimental results substantiate the superiority of the authors' proposed algorithm compared to various algorithms used in practice and discussed in the relevant literature. Moreover, optimal system configurations for the instances generated are suggested.Keywords: Compact storage systemrobot dispatchingdual-commandadaptive neighbourhood search AcknowledgementsDongjun Cai thanks his industrial supervisor, Dr Ng Ging Meng, who provided supportive suggestions and the resources needed to carry out the work. They also express immense gratitude to their research supervisor and mentor, the late Professor Loo Hay Lee, for providing patient guidance, advice and encouragement throughout this study.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article. No new data were created or analysed in this study.Additional informationFundingXi Xiang is supported by the National Natural Science Foundation of China [Grant No. 72301029]. Dongjun Cai is supported by the funding of the Centre of Excellence in Modelling and Simulation for Next Generation Ports [Grant No. 3030012222341].
{"title":"Robot dispatching problem for compact storage and retrieval systems with dual-command transactions","authors":"Dongjun Cai, Xi Xiang, Loo Hay Lee, Ek Peng Chew, Kok Choon Tan","doi":"10.1080/0305215x.2023.2269849","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2269849","url":null,"abstract":"AbstractA robotic compact storage and retrieval system (RCSRS) is a grid-based system that has been popularly implemented by online retailers around the world recently. This article addresses a robot dispatching problem for RCSRS, aiming to reduce robot empty travelling time and workstation idle time. The robot dispatching problem is to assign tasks to robots when the task sequences in workstations are given. Additionally, the robots follow a fast dual-command transaction process in this problem. Hence, a mixed integer programming model catering for the dual-command transaction process is formulated to optimize system performance. Furthermore, an adaptive neighbourhood search with an ε-greedy algorithm is proposed to solve the problem. The experimental results substantiate the superiority of the authors' proposed algorithm compared to various algorithms used in practice and discussed in the relevant literature. Moreover, optimal system configurations for the instances generated are suggested.Keywords: Compact storage systemrobot dispatchingdual-commandadaptive neighbourhood search AcknowledgementsDongjun Cai thanks his industrial supervisor, Dr Ng Ging Meng, who provided supportive suggestions and the resources needed to carry out the work. They also express immense gratitude to their research supervisor and mentor, the late Professor Loo Hay Lee, for providing patient guidance, advice and encouragement throughout this study.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article. No new data were created or analysed in this study.Additional informationFundingXi Xiang is supported by the National Natural Science Foundation of China [Grant No. 72301029]. Dongjun Cai is supported by the funding of the Centre of Excellence in Modelling and Simulation for Next Generation Ports [Grant No. 3030012222341].","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"3 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136348020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-10DOI: 10.1080/0305215x.2023.2276430
Ali Panchami Afra, Amirsaman Kheirkhah
AbstractEffective decision making in large project planning presents a significant challenge. Despite progress in developing mathematical models, few studies comprehensively address project and supply-chain management aspects in an integrated framework. This article presents an integrated approach for multi-project resource investment, material ordering and production planning in a project-driven supply chain. A mixed-integer programming model is developed to optimize the total cost of renewable resource investment, production, transportation, and material ordering and holding, with an opportunity to share mobile renewable resources across multiple projects. A Lagrangian relaxation heuristic algorithm is proposed to determine the upper and lower bounds for the objective function, with an additional set of valid cuts to reduce the distance between bounds. The results of numerical experiments demonstrate the favourable performance of the proposed algorithm compared to the GAMS solver. This article provides insights into supply-chain participant expenses and activity scheduling based on these findings.KEYWORDS: Project-driven supply chainmulti-project resource investmentmaterial orderingproduction planningLagrangian relaxation Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article.
{"title":"A Lagrangian heuristic for integrated production planning, material ordering and investment multi-project scheduling in a project-driven supply chain","authors":"Ali Panchami Afra, Amirsaman Kheirkhah","doi":"10.1080/0305215x.2023.2276430","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2276430","url":null,"abstract":"AbstractEffective decision making in large project planning presents a significant challenge. Despite progress in developing mathematical models, few studies comprehensively address project and supply-chain management aspects in an integrated framework. This article presents an integrated approach for multi-project resource investment, material ordering and production planning in a project-driven supply chain. A mixed-integer programming model is developed to optimize the total cost of renewable resource investment, production, transportation, and material ordering and holding, with an opportunity to share mobile renewable resources across multiple projects. A Lagrangian relaxation heuristic algorithm is proposed to determine the upper and lower bounds for the objective function, with an additional set of valid cuts to reduce the distance between bounds. The results of numerical experiments demonstrate the favourable performance of the proposed algorithm compared to the GAMS solver. This article provides insights into supply-chain participant expenses and activity scheduling based on these findings.KEYWORDS: Project-driven supply chainmulti-project resource investmentmaterial orderingproduction planningLagrangian relaxation Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article.","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"121 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135136295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-26DOI: 10.1080/0305215x.2023.2269844
Ke Zhang, Bin Chai, Minghu Tan, Ye Zhang, Jingyu Wang
AbstractPath planning with multiple evaluation metrics makes the motion of a robot realistic, but the contradiction between the metrics and the lack of global search and obstacle avoidance capabilities increases the difficulty of obtaining the optimization solution. To solve these problems, an enhanced ant colony algorithm (EACA) with an obstacle avoidance strategy is proposed in this article. First, the path planning model is constructed, and strict movement rules are designed. Secondly, the EACA with global search, balancing the contradiction between metrics, is designed. The dynamic regulation of pheromone concentration and the mechanism of fluctuating pheromone distribution are explored, heuristic information is optimized and the path planning effect is enhanced. Finally, a new mechanism of away-from-obstacles is proposed as the obstacle avoidance strategy, which ensures a reasonable safe distance. Comparative simulations on several different maps validate the performance of EACA with the obstacle avoidance strategy for planning robot movement paths.KEYWORDS: Enhanced ant colony algorithmobstacle avoidance strategypath planningmulti-objectiveoptimal AcknowledgementsThe authors are deeply grateful to the anonymous reviewers for their valuable comments and suggestions, which greatly enhanced the quality of this article.Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementAll data generated or analysed during this study are included in this published article.
{"title":"Enhanced ant colony algorithm with obstacle avoidance strategy for multi-objective path planning of mobile robots","authors":"Ke Zhang, Bin Chai, Minghu Tan, Ye Zhang, Jingyu Wang","doi":"10.1080/0305215x.2023.2269844","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2269844","url":null,"abstract":"AbstractPath planning with multiple evaluation metrics makes the motion of a robot realistic, but the contradiction between the metrics and the lack of global search and obstacle avoidance capabilities increases the difficulty of obtaining the optimization solution. To solve these problems, an enhanced ant colony algorithm (EACA) with an obstacle avoidance strategy is proposed in this article. First, the path planning model is constructed, and strict movement rules are designed. Secondly, the EACA with global search, balancing the contradiction between metrics, is designed. The dynamic regulation of pheromone concentration and the mechanism of fluctuating pheromone distribution are explored, heuristic information is optimized and the path planning effect is enhanced. Finally, a new mechanism of away-from-obstacles is proposed as the obstacle avoidance strategy, which ensures a reasonable safe distance. Comparative simulations on several different maps validate the performance of EACA with the obstacle avoidance strategy for planning robot movement paths.KEYWORDS: Enhanced ant colony algorithmobstacle avoidance strategypath planningmulti-objectiveoptimal AcknowledgementsThe authors are deeply grateful to the anonymous reviewers for their valuable comments and suggestions, which greatly enhanced the quality of this article.Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementAll data generated or analysed during this study are included in this published article.","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136381138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.1080/0305215x.2023.2269847
João Marcos Pereira Silva, Anand Subramanian, Eduardo Uchoa
AbstractThis article studies the problem of scheduling independent jobs on parallel machines with a common server, the objective of which is to minimize the makespan. In this case, the common server is responsible for performing the setup operations and, therefore, there must be no conflicts while conducting them. Four alternative time-indexed formulations for the problem are considered and evaluated computationally. Moreover, two algorithms are presented that can significantly improve the performance of the best time-indexed formulation. The results obtained on two benchmark datasets involving up to 100 jobs suggest that the proposed improved algorithms are substantially better than existing approaches.Keywords: Schedulingparallel machinescommon servertime-indexed formulationsinteger programming Disclosure statementThe authors declare that they have no conflict of interest.Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article.Additional informationFundingThis research was partially supported by Comissão de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) [Grant Finance Code 001]; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) [Grants 428549/2016-0, 307843/2018-1 and 313601/2018-6]; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (Faperj) [Grant E-26/202.887/2017]; [CAPES PrInt UFF No 88881].
摘要本文研究了具有公共服务器的并行机上独立作业的调度问题，其目标是最小化完工时间。在这种情况下，公共服务器负责执行设置操作，因此，在执行这些操作时必须没有冲突。对该问题的四种备选时间索引公式进行了考虑和计算评估。此外，提出了两种算法，可以显著提高最佳时间索引公式的性能。在涉及多达100个作业的两个基准数据集上获得的结果表明，所提出的改进算法比现有方法要好得多。关键词:调度并行机通用服务器时间索引公式整数编程公开声明作者声明他们没有利益冲突。数据可用性声明作者确认在文章中可以获得支持本研究结果的数据。本研究的部分资金由高级财务管理委员会Nível (CAPES)[资助财务法001]提供支持;国家环境保护研究中心Científico e Tecnológico (CNPq)[拨款428549/2016- 0,307843 /2018-1和313601/2018-6];巴西里约热内卢州政府基金(Faperj) [Grant E-26/202.887/2017];[CAPES PrInt UFF No 88881]。
{"title":"On time-indexed formulations for the parallel machine scheduling problem with a common server","authors":"João Marcos Pereira Silva, Anand Subramanian, Eduardo Uchoa","doi":"10.1080/0305215x.2023.2269847","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2269847","url":null,"abstract":"AbstractThis article studies the problem of scheduling independent jobs on parallel machines with a common server, the objective of which is to minimize the makespan. In this case, the common server is responsible for performing the setup operations and, therefore, there must be no conflicts while conducting them. Four alternative time-indexed formulations for the problem are considered and evaluated computationally. Moreover, two algorithms are presented that can significantly improve the performance of the best time-indexed formulation. The results obtained on two benchmark datasets involving up to 100 jobs suggest that the proposed improved algorithms are substantially better than existing approaches.Keywords: Schedulingparallel machinescommon servertime-indexed formulationsinteger programming Disclosure statementThe authors declare that they have no conflict of interest.Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article.Additional informationFundingThis research was partially supported by Comissão de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) [Grant Finance Code 001]; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) [Grants 428549/2016-0, 307843/2018-1 and 313601/2018-6]; Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (Faperj) [Grant E-26/202.887/2017]; [CAPES PrInt UFF No 88881].","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135265951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-09DOI: 10.1080/0305215x.2023.2260992
Ibrahim Mlaouhi, Najeh Ben Guedria, Chokri Bouraoui
AbstractEnhancing the vibration behaviour of rotating systems while meeting conflicting design needs is a difficult task, which is often treated as an inverse issue and formulated as a nonlinear optimization problem with constraints. To tackle this intricate challenge, a novel hybrid algorithm (HDE-Jaya) has been developed, combining the differential evolution (DE) and Jaya methods. The Jaya model is integrated into DE as a mutation operator to boost exploration and exploitation. In addition, the crossover probability is generated randomly at each iteration to preserve diversity. This makes HDE-Jaya a parameter-free algorithm. The performance of HDE-Jaya was validated by optimizing six common mechanical engineering design problems and further evaluated on an automotive turbocharger design, aiming to reduce vibrations, minimize binding stress and improve dynamic stability. The results indicate that HDE-Jaya is superior to other algorithms, including DE and the Jaya algorithm, in terms of solution accuracy and computational efficiency.KEYWORDS: Design optimizationinverse problemHDE-Jayaautomotive turbochargervibration level Data availability statementThe authors affirm that the data backing the results of the study can be found on figshare at: https://figshare.com/s/b9694bf562486d1a4254Disclosure statementNo potential conflict of interest was reported by the authors.
{"title":"An efficient hybrid differential evolution–Jaya algorithm for enhancing vibration behaviour in automotive turbocharger systems","authors":"Ibrahim Mlaouhi, Najeh Ben Guedria, Chokri Bouraoui","doi":"10.1080/0305215x.2023.2260992","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2260992","url":null,"abstract":"AbstractEnhancing the vibration behaviour of rotating systems while meeting conflicting design needs is a difficult task, which is often treated as an inverse issue and formulated as a nonlinear optimization problem with constraints. To tackle this intricate challenge, a novel hybrid algorithm (HDE-Jaya) has been developed, combining the differential evolution (DE) and Jaya methods. The Jaya model is integrated into DE as a mutation operator to boost exploration and exploitation. In addition, the crossover probability is generated randomly at each iteration to preserve diversity. This makes HDE-Jaya a parameter-free algorithm. The performance of HDE-Jaya was validated by optimizing six common mechanical engineering design problems and further evaluated on an automotive turbocharger design, aiming to reduce vibrations, minimize binding stress and improve dynamic stability. The results indicate that HDE-Jaya is superior to other algorithms, including DE and the Jaya algorithm, in terms of solution accuracy and computational efficiency.KEYWORDS: Design optimizationinverse problemHDE-Jayaautomotive turbochargervibration level Data availability statementThe authors affirm that the data backing the results of the study can be found on figshare at: https://figshare.com/s/b9694bf562486d1a4254Disclosure statementNo potential conflict of interest was reported by the authors.","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135095256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-06DOI: 10.1080/0305215x.2023.2262389
Suo Zhang, Dejian Meng, Yunkai Gao, James Yang, Xiang Xu
AbstractAn ideal theoretical model integrating four revolute joints is developed to capture the kinematic behaviour of a vehicle scissor door joint mechanism. Then, triaxial acceleration experiments are conducted to validate the effectiveness of the developed theoretical model. Furthermore, to improve dynamic responses of the mechanism, a novel discrete multi-objective optimization (DMO) method is proposed to address optimization problems where design variables cannot be parameterized. This method integrates the Taguchi method, grey relational analysis and a hybrid multi-objective decision-making approach, and iteratively updates the orthogonal array to perform optimization for handling design variables with multiple levels. Compared to the conventional non-dominated sorting genetic algorithm-II (NSGA-II), the developed DMO is capable of achieving the Pareto frontier with fewer evaluations of the objective function. The optimization results reveal that the optimized design for the electric and gas struts exhibits favourable dynamic responses of scissor door operation compared to the initial design.KEYWORDS: Ideal theoretical modeljoint mechanismdiscrete multi-objective optimization (DMO)Taguchi method Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementThe data used to support the findings of this study are included in this article.AcknowledgementThe support for this work from the National Natural Science Foundation of China is greatly appreciated.Additional informationFundingThis work was supported by the National Natural Science Foundation of China [grant numbers 51975438, 52305244].
{"title":"Modelling and novel multi-level discrete optimization method for vehicle scissor door joint mechanism","authors":"Suo Zhang, Dejian Meng, Yunkai Gao, James Yang, Xiang Xu","doi":"10.1080/0305215x.2023.2262389","DOIUrl":"https://doi.org/10.1080/0305215x.2023.2262389","url":null,"abstract":"AbstractAn ideal theoretical model integrating four revolute joints is developed to capture the kinematic behaviour of a vehicle scissor door joint mechanism. Then, triaxial acceleration experiments are conducted to validate the effectiveness of the developed theoretical model. Furthermore, to improve dynamic responses of the mechanism, a novel discrete multi-objective optimization (DMO) method is proposed to address optimization problems where design variables cannot be parameterized. This method integrates the Taguchi method, grey relational analysis and a hybrid multi-objective decision-making approach, and iteratively updates the orthogonal array to perform optimization for handling design variables with multiple levels. Compared to the conventional non-dominated sorting genetic algorithm-II (NSGA-II), the developed DMO is capable of achieving the Pareto frontier with fewer evaluations of the objective function. The optimization results reveal that the optimized design for the electric and gas struts exhibits favourable dynamic responses of scissor door operation compared to the initial design.KEYWORDS: Ideal theoretical modeljoint mechanismdiscrete multi-objective optimization (DMO)Taguchi method Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementThe data used to support the findings of this study are included in this article.AcknowledgementThe support for this work from the National Natural Science Foundation of China is greatly appreciated.Additional informationFundingThis work was supported by the National Natural Science Foundation of China [grant numbers 51975438, 52305244].","PeriodicalId":50521,"journal":{"name":"Engineering Optimization","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135351113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-05DOI: 10.1080/0305215x.2023.2258067
Ge Hong, Shuo Gao, Tangbin Xia, Juan Du, Xuancheng Jin, Ershun Pan, Lifeng Xi
AbstractFixture layout is an essential factor in intelligent manufacturing in the shipbuilding industry, affecting assembly quality and efficiency. Its optimization has become an urgent problem in the assembly process of compliant parts. Traditional fixture layout depends on workers’ experience, which leads to butt clearance along the assembly interface. Thus, this article proposes a butt clearance control-oriented fixture layout optimization (BCCFLO) methodology. First, a method for calculating the part dimensional variation under the influence of fixture layout and fixture locating error is developed. Then, a constrained multi-objective integer nonlinear programming (CMINP) model is innovatively formulated to optimize the fixture layout. Furthermore, the non-dominated sorting genetic algorithm-II based on Latin hypercube sampling is designed to address the CMINP model. The case study illustrates and validates that the fixture layout achieved by the proposed method could significantly control the butt clearance for large compliant part assembly in the shipbuilding industry.KEYWORDS: Compliant part assemblyfixture layout optimizationbutt clearance controlfinite element equationlarge ship panels AcknowledgementsThis research is supported by the National Key Research and Development Program of China [2022YFF0605700], National Natural Science Foundation of China [51875359 and 72001139], Natural Science Foundation of Shanghai [20ZR1428600], CSSC-SJTU Marine Equipment Forward Looking Innovation Foundation [22B010432] and Oceanic Interdisciplinary Program of Shanghai Jiao Tong University [SL2021MS008].Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article.Additional informationFundingThis work was supported by the National Key Research and Development Program of China [grant number 2022YFF0605700]; National Natural Science Foundation of China [grant number 51875359]; Natural Science Foundation of Shanghai Municipality [grant number 20ZR1428600]; CSSC-SJTU Marine Equipment Forward Looking Innovation Foundation [grant number 22B010432]; Oceanic Interdisciplinary Program of Shanghai Jiao Tong University [grant number SL2021MS008].
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