复杂系统建模与仿真(英文)最新文献_第10页

Evaluation System and Correlation Analysis for Determining the Performance of a Semiconductor Manufacturing System 半导体制造系统性能评价体系及相关分析

复杂系统建模与仿真(英文) Pub Date : 2021-09-01 DOI: 10.23919/CSMS.2021.0015

Qingyun Yu;Li Li;Hui Zhao;Ying Liu;Kuo-Yi Lin

{"title":"Evaluation System and Correlation Analysis for Determining the Performance of a Semiconductor Manufacturing System","authors":"Qingyun Yu;Li Li;Hui Zhao;Ying Liu;Kuo-Yi Lin","doi":"10.23919/CSMS.2021.0015","DOIUrl":"10.23919/CSMS.2021.0015","url":null,"abstract":"Numerous performance indicators exist for semiconductor manufacturing systems. Several studies have been conducted regarding the performance optimization of semiconductor manufacturing systems. However, because of the complex manufacturing processes, potential complementary or inhibitory correlations may exist among performance indicators, which are difficult to demonstrate specifically. To analyze the correlation between the performance indicators, this study proposes a performance evaluation system based on the mathematical significance of each performance indicator to design statistical schemes. Several samples can be obtained by conducting simulation experiments through the performance evaluation system. The Pearson correlation coefficient method and canonical correlation analysis are used on the received samples to analyze linear correlations between the performance indicators. Through the investigation, we found that linear and other complex correlations exist between the performance indicators. This finding can contribute to our future studies regarding performance optimization for the scheduling problems of semiconductor manufacturing.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"218-231"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600619.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41594524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Multicommodity Flow Modeling for the Data Transmission Scheduling Problem in Navigation Satellite Systems 卫星导航系统数据传输调度问题的多商品流建模

复杂系统建模与仿真(英文) Pub Date : 2021-09-01 DOI: 10.23919/CSMS.2021.0019

Jungang Yan;Lining Xing;Chao Li;Zhongshan Zhang

引用次数: 3

Multidirection Update-Based Multiobjective Particle Swarm Optimization for Mixed No-Idle Flow-Shop Scheduling Problem 基于多方向更新的混合无空闲流车间调度问题多目标粒子群优化

复杂系统建模与仿真(英文) Pub Date : 2021-09-01 DOI: 10.23919/CSMS.2021.0017

Wenqiang Zhang;Wenlin Hou;Chen Li;Weidong Yang;Mitsuo Gen

{"title":"Multidirection Update-Based Multiobjective Particle Swarm Optimization for Mixed No-Idle Flow-Shop Scheduling Problem","authors":"Wenqiang Zhang;Wenlin Hou;Chen Li;Weidong Yang;Mitsuo Gen","doi":"10.23919/CSMS.2021.0017","DOIUrl":"10.23919/CSMS.2021.0017","url":null,"abstract":"The Mixed No-Idle Flow-shop Scheduling Problem (MNIFSP) is an extension of flow-shop scheduling, which has practical significance and application prospects in production scheduling. To improve the efficacy of solving the complicated multiobjective MNIFSP, a MultiDirection Update (MDU) based Multiobjective Particle Swarm Optimization (MDU-MoPSO) is proposed in this study. For the biobjective optimization problem of the MNIFSP with minimization of makespan and total processing time, the MDU strategy divides particles into three subgroups according to a hybrid selection mechanism. Each subgroup prefers one convergence direction. Two subgroups are individually close to the two edge areas of the Pareto Front (PF) and serve two objectives, whereas the other one approaches the central area of the PF, preferring the two objectives at the same time. The MDU-MoPSO adopts a job sequence representation method and an exchange sequence-based particle update operation, which can better reflect the characteristics of sequence differences among particles. The MDU-MoPSO updates the particle in multiple directions and interacts in each direction, which speeds up the convergence while maintaining a good distribution performance. The experimental results and comparison of six classical evolutionary algorithms for various benchmark problems demonstrate the effectiveness of the proposed algorithm.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"176-197"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600624.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48775142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Call for Papers: Special Issue on Computational Intelligence Methods for Big Data Analytics under Uncertain Environments 论文征集：不确定环境下大数据分析的计算智能方法特刊

复杂系统建模与仿真(英文) Pub Date : 2021-09-01 DOI: 10.23919/CSMS.2021.0021

引用次数: 0

Call for Papers: Special Issue on Intelligent Optimization, Modeling, and Simulation with Knowledge for Complex Systems 论文征集:关于复杂系统知识的智能优化、建模和仿真的特刊

复杂系统建模与仿真(英文) Pub Date : 2021-09-01 DOI: 10.23919/CSMS.2021.0020

引用次数: 1

Distributed Flow Shop Scheduling with Sequence-Dependent Setup Times Using an Improved Iterated Greedy Algorithm 基于改进迭代贪心算法的序列依赖的分布式流水车间调度

复杂系统建模与仿真(英文) Pub Date : 2021-09-01 DOI: 10.23919/CSMS.2021.0018

Xue Han;Yuyan Han;Qingda Chen;Junqing Li;Hongyan Sang;Yiping Liu;Quanke Pan;Yusuke Nojima

{"title":"Distributed Flow Shop Scheduling with Sequence-Dependent Setup Times Using an Improved Iterated Greedy Algorithm","authors":"Xue Han;Yuyan Han;Qingda Chen;Junqing Li;Hongyan Sang;Yiping Liu;Quanke Pan;Yusuke Nojima","doi":"10.23919/CSMS.2021.0018","DOIUrl":"10.23919/CSMS.2021.0018","url":null,"abstract":"To meet the multi-cooperation production demand of enterprises, the distributed permutation flow shop scheduling problem (DPFSP) has become the frontier research in the field of manufacturing systems. In this paper, we investigate the DPFSP by minimizing a makespan criterion under the constraint of sequence-dependent setup times. To solve DPFSPs, significant developments of some metaheuristic algorithms are necessary. In this context, a simple and effective improved iterated greedy (NIG) algorithm is proposed to minimize makespan in DPFSPs. According to the features of DPFSPs, a two-stage local search based on single job swapping and job block swapping within the key factory is designed in the proposed algorithm. We compare the proposed algorithm with state-of-the-art algorithms, including the iterative greedy algorithm (2019), iterative greedy proposed by Ruiz and Pan (2019), discrete differential evolution algorithm (2018), discrete artificial bee colony (2018), and artificial chemical reaction optimization (2017). Simulation results show that NIG outperforms the compared algorithms.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"198-217"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600643.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43796166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 49

Review of Dynamic Task Allocation Methods for UAV Swarms Oriented to Ground Targets 面向地面目标的无人机机群动态任务分配方法综述

复杂系统建模与仿真(英文) Pub Date : 2021-09-01 DOI: 10.23919/CSMS.2021.0022

Qiang Peng;Husheng Wu;Ruisong Xue

{"title":"Review of Dynamic Task Allocation Methods for UAV Swarms Oriented to Ground Targets","authors":"Qiang Peng;Husheng Wu;Ruisong Xue","doi":"10.23919/CSMS.2021.0022","DOIUrl":"10.23919/CSMS.2021.0022","url":null,"abstract":"Dynamic task allocation of unmanned aerial vehicle swarms for ground targets is an important part of unmanned aerial vehicle (UAV) swarms task planning and the key technology to improve autonomy. The realization of dynamic task allocation in UAV swarms for ground targets is very difficult because of the large uncertainty of swarms, the target and environment state, and the high real-time allocation requirements. Hence, dynamic task allocation of UAV swarms oriented to ground targets has become a key and difficult problem in the field of mission planning. In this work, a dynamic task allocation method for UAV swarms oriented to ground targets is comprehensively and systematically summarized from two aspects: the establishment of an allocation model and the solution of the allocation model. First, the basic concept and trigger scenario are introduced. Second, the research status and the advantages and disadvantages of the two allocation models are analyzed. Third, the research status and the advantages and disadvantages of several common dynamic task allocation algorithms, such as the algorithm based on market mechanisms, intelligent optimization algorithm, and clustering algorithm, are evaluated. Finally, the specific problems of the current UAV swarm dynamic task allocation method for ground targets are highlighted, and future research directions are established. This work offers important reference significance for fully understanding the current situation of UAV swarm dynamic task allocation technology.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 3","pages":"163-175"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9600623/09600625.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48534144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Optimization Landscape of Quantum Control Systems 量子控制系统的优化景观

复杂系统建模与仿真(英文) Pub Date : 2021-06-01 DOI: 10.23919/CSMS.2021.0014

Xiaozhen Ge;Rebing Wu;Herschel Rabitz

引用次数: 3

A Novel Cooperative Multi-Stage Hyper-Heuristic for Combination Optimization Problems 组合优化问题的一种新型协同多阶段超启发式算法

复杂系统建模与仿真(英文) Pub Date : 2021-06-01 DOI: 10.23919/CSMS.2021.0010

Fuqing Zhao;Shilu Di;Jie Cao;Jianxin Tang;Jonrinaldi

{"title":"A Novel Cooperative Multi-Stage Hyper-Heuristic for Combination Optimization Problems","authors":"Fuqing Zhao;Shilu Di;Jie Cao;Jianxin Tang;Jonrinaldi","doi":"10.23919/CSMS.2021.0010","DOIUrl":"10.23919/CSMS.2021.0010","url":null,"abstract":"A hyper-heuristic algorithm is a general solution framework that adaptively selects the optimizer to address complex problems. A classical hyper-heuristic framework consists of two levels, including the high-level heuristic and a set of low-level heuristics. The low-level heuristics to be used in the optimization process are chosen by the high-level tactics in the hyper-heuristic. In this study, a Cooperative Multi-Stage Hyper-Heuristic (CMS-HH) algorithm is proposed to address certain combinatorial optimization problems. In the CMS-HH, a genetic algorithm is introduced to perturb the initial solution to increase the diversity of the solution. In the search phase, an online learning mechanism based on the multi-armed bandits and relay hybridization technology are proposed to improve the quality of the solution. In addition, a multi-point search is introduced to cooperatively search with a single-point search when the state of the solution does not change in continuous time. The performance of the CMS-HH algorithm is assessed in six specific combinatorial optimization problems, including Boolean satisfiability problems, one-dimensional packing problems, permutation flow-shop scheduling problems, personnel scheduling problems, traveling salesman problems, and vehicle routing problems. The experimental results demonstrate the efficiency and significance of the proposed CMS-HH algorithm.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 2","pages":"91-108"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.23919/CSMS.2021.0010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43278531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 50

Scheduling Storage Process of Shuttle-Based Storage and Retrieval Systems Based on Reinforcement Learning 基于强化学习的梭式存储检索系统存储过程调度

复杂系统建模与仿真(英文) Pub Date : 2021-06-01 DOI: 10.23919/CSMS.2021.0013

Lei Luo;Ning Zhao;Gabriel Lodewijks

{"title":"Scheduling Storage Process of Shuttle-Based Storage and Retrieval Systems Based on Reinforcement Learning","authors":"Lei Luo;Ning Zhao;Gabriel Lodewijks","doi":"10.23919/CSMS.2021.0013","DOIUrl":"10.23919/CSMS.2021.0013","url":null,"abstract":"The Shuttle-Based Storage and Retrieval System (SBS/RS) has been widely studied because it is currently the most efficient automated warehousing system. Most of the related existing studies are focused on the prediction and improvement of the efficiency of such a system at the design stage. Hence, the control of existing SBS/RSs has been rarely investigated. In existing SBS/RSs, some empirical rules, such as storing loads column by column, are used to control or schedule the storage process. The question is whether or not the control of the storage process in an existing system can be improved further by using a different approach. The storage process is controlled to minimize the makespan of storing a series of loads into racks. Empirical storage rules are easy to control, but they do not reach the minimum makespan. In this study, the performance of a control system that uses reinforcement learning to schedule the storage process of an SBS/RS with fixed configurations is evaluated. Specifically, a reinforcement learning algorithm called the actor-critic algorithm is used. This algorithm is made up of two neural networks and is effective in making decisions and updating itself. It can also reduce the makespan relative to the existing empirical rules used to improve system performance. Experiment results show that in an SBS/RS comprising six columns and six tiers and featuring a storage capacity of 72 loads, the actor-critic algorithm can reduce the makespan by 6.67% relative to the column-by-column storage rule. The proposed algorithm also reduces the makespan by more than 30% when the number of loads being stored is in the range of 7-45, which is equal to 9.7%-62.5% of the systems' storage capacity.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"1 2","pages":"131-144"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.23919/CSMS.2021.0013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43439508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3