复杂系统建模与仿真(英文)最新文献_第3页

Ensemble Artificial Bee Colony Algorithm and Q-Learning for Multi-Objective Distributed Heterogeneous Flowshop Scheduling Problems with Sequence-Dependent Setup Time 集合人工蜂群算法与q -学习用于序列依赖的多目标分布式异构流水车间调度问题

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2024.0040

Fubin Liu;Kaizhou Gao;Adam Słowik;Ponnuthurai Nagaratnam Suganthan

{"title":"Ensemble Artificial Bee Colony Algorithm and Q-Learning for Multi-Objective Distributed Heterogeneous Flowshop Scheduling Problems with Sequence-Dependent Setup Time","authors":"Fubin Liu;Kaizhou Gao;Adam Słowik;Ponnuthurai Nagaratnam Suganthan","doi":"10.23919/CSMS.2024.0040","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0040","url":null,"abstract":"As the global economy develops and people's awareness of environmental protection increases, the efficient scheduling of production lines in workshops has received more and more attention. However, there is very little research focusing on distributed scheduling for heterogeneous factories. This study addresses a multi-objective distributed heterogeneous permutation flow shop scheduling problem with sequence-dependent setup times (DHPFSP-SDST). The objective is to optimize the trade-off between the maximum completion time (Makespan) and total energy consumption. First, to describe the concerned problems, we establish a mathematical model. Second, we use the artificial bee colony (ABC) algorithm to optimize the two objectives, incorporating five local search strategies tailored to the problem characteristics to enhance the algorithm's performance. Third, to improve the convergence speed of the algorithm, a Q-learning based strategy is designed to select the appropriated local search operator during iterations. Finally, based on experiments conducted on 72 instances, statistical analysis and discussions show that the Q-learning based ABC algorithm can effectively solve the problems better than its peers.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"5 3","pages":"221-235"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10969533","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896788","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: 0

Modeling and Analyzing Multi-Factor Balanced Feedback System Based on Petri Net 基于Petri网的多因素平衡反馈系统建模与分析

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2024.0035

Yumeng Cheng;Wangyang Yu;Xianwen Fang;Qi Guo;Beiming Zhang

{"title":"Modeling and Analyzing Multi-Factor Balanced Feedback System Based on Petri Net","authors":"Yumeng Cheng;Wangyang Yu;Xianwen Fang;Qi Guo;Beiming Zhang","doi":"10.23919/CSMS.2024.0035","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0035","url":null,"abstract":"Process control systems typically comprise multiple variables that impact system parameters, interacting and constraining each other with the objective of maintaining parameters within a specified range to ensure dynamic equilibrium. The reliability and safety of these systems are also of paramount concern. The multi-factor Balanced Feedback Net (BFN) represents one of the significant models for simulating systems with balanced feedback mechanisms. This paper refines and expands the definition of BFN, creating BFN models that incorporate varying quantities of balance factors. Based on this, we analyze the structural properties of BFN and provide relevant proofs. Given the complexity of BFN modeling, this paper introduces an innovative approach to translating real-world process control systems into BFN and develops an algorithm to assist users in automatically constructing BFN. For extreme situations that may arise in process control systems, we present an early recognition algorithm for extreme states in BFN. Theoretical proofs and case analyses complement each other, as demonstrated by the example of the water level control system of a steam boiler. This illustrates the effectiveness of methods and algorithms in complex system control and optimization.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"5 4","pages":"323-339"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10969578","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145705896","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: 0

RM-MOCO: A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on Retention 基于保留的神经网络多目标组合优化快速求解模型

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2024.0029

Huiqing Wei;Fei Han;Qing Liu;Henry Han

{"title":"RM-MOCO: A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on Retention","authors":"Huiqing Wei;Fei Han;Qing Liu;Henry Han","doi":"10.23919/CSMS.2024.0029","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0029","url":null,"abstract":"Multiobjective combinatorial optimization (MOCO) problems have a wide range of applications in the real world. Recently, learning-based methods have achieved good results in solving MOCO problems. However, most of these methods use attention mechanisms and their variants, which have room for further improvement in the speed of solving MOCO problems. In this paper, following the idea of decomposition strategy and neural combinatorial optimization, a novel fast-solving model for MOCO based on retention is proposed. A brand new calculation of retention is proposed, causal masking and exponential decay are deprecated in retention, so that our model could better solve MOCO problems. During model training, a parallel computation of retention is applied, allowing for fast parallel training. When using the model to solve MOCO problems, a recurrent computation of retention is applied, enabling quicker problem-solving. In order to make our model more practical and flexible, a preference-based retention decoder is proposed, which allows generating approximate Pareto solutions for any trade-off preferences directly. An industry-standard deep reinforcement learning algorithm is used to train RM-MOCO. Experimental results show that, while ensuring the quality of problem solving, the proposed method significantly outperforms some other methods in terms of the speed of solving MOCO problems.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"5 2","pages":"125-137"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10969587","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937969","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: 0

Learning-Based Automated Program Repair: A Systematic Literature Review 基于学习的自动程序修复：系统的文献综述

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2025.0004

Qijia Chen;Dongcheng Li;Man Zhao;W. Eric Wong;Hui Li

引用次数: 0

Color Image Encryption Based on Five-Dimensional Continuous Hyperchaotic System and Optimized Arnold Algorithm 基于五维连续超混沌系统和优化Arnold算法的彩色图像加密

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2024.0028

Zhenju Wang;Cong Wang;Ping Ma;Yue Meng;Hongli Zhang

{"title":"Color Image Encryption Based on Five-Dimensional Continuous Hyperchaotic System and Optimized Arnold Algorithm","authors":"Zhenju Wang;Cong Wang;Ping Ma;Yue Meng;Hongli Zhang","doi":"10.23919/CSMS.2024.0028","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0028","url":null,"abstract":"This paper introduces a novel color image encryption algorithm based on a five-dimensional continuous memristor hyperchaotic system (5D-MHS), combined with a two-dimensional Salomon map and an optimized Arnold transform. Firstly, convert the test image to a 2D pixel matrix then processed in blocks, and each block of the pixel matrix is permuted with chaotic sequences generated by 5D-MHS and 2D Salomon map. Then, the permuted image is permuted for three rounds with the optimized Arnold algorithm. Finally, one of the chaotic sequences generated by 5D-MHS is employed to diffuse the permuted image to obtain the final ciphertext image. In this paper, several pseudo-random sequences are generated and mixed in the permutation stage to achieve higher security. The algorithm achieves a key space of 2<sup>472</sup>, the information entropy of the ciphertext image for the color image is 7.9998, number of pixels change rate (NPCR) and unified average changing intensity (UACI) reached 99.6131 % and 33.4361 %, respectively, and the correlation between pixels is close to O. The simulation results show that the encryption algorithm is efficient and the key system is secure.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"5 2","pages":"138-154"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10969590","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937986","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: 0

Novel Consensus-Based Particle Swarm Optimization-Guided Surrogate-Enhanced Methodology for Solving Expensive Black-Box Optimization 基于共识的粒子群优化导向的新型代理增强方法求解昂贵的黑盒优化

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2025.0006

Yongfeng Zhang;Zhihao Liu;Kaili Jia;Zhenbin Zhang;Hsiaodong Chiang

引用次数: 0

Towards Calibrating Financial Market Simulators with High-Frequency Data 用高频数据校准金融市场模拟器

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2025.0002

Peng Yang;Junji Ren;Feng Wang;Ke Tang

引用次数: 0

Bistatic Echo Simulation Method of Micro-Motion Target with Specular Scattering Conditions 具有镜面散射条件的微运动目标双基地回波仿真方法

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2024.0038

Yiqi Zhu;Zhiming Xu;Xiaofeng Ai;Xiaoxia Xie;Feng Zhao;Jinhui Zhao

引用次数: 0

Synchronization in Memristive Small-World Neural Networks Under Electromagnetic Radiation 电磁辐射下记忆性小世界神经网络的同步

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2024.0036

Jiapeng Ouyang;Yalian Wu;Yichuang Sun;Minglin Ma

引用次数: 0

Novel Hybrid Algorithm of Cooperative Evolutionary Algorithm and Constraint Programming for Dual Resource Constrained Flexible Job Shop Scheduling Problems 双资源约束柔性作业车间调度问题的协同进化算法与约束规划混合算法

复杂系统建模与仿真(英文) Pub Date : 2025-04-17 DOI: 10.23919/CSMS.2024.0041

Changao Li;Leilei Meng;Saif Ullah;Peng Duan;Biao Zhang;Hongyan Sang

{"title":"Novel Hybrid Algorithm of Cooperative Evolutionary Algorithm and Constraint Programming for Dual Resource Constrained Flexible Job Shop Scheduling Problems","authors":"Changao Li;Leilei Meng;Saif Ullah;Peng Duan;Biao Zhang;Hongyan Sang","doi":"10.23919/CSMS.2024.0041","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0041","url":null,"abstract":"In real production, machines are operated by workers, and the constraints of worker flexibility should be considered. The flexible job shop scheduling problem with both machine and worker resources (DRCFJSP) has become a research hotspot in recent years. In this paper, DRCFJSP with the objective of minimizing the makespan is studied, and it should solve three sub-problems: machine allocation, worker allocation, and operations sequencing. To solve DRCFJSP, a novel hybrid algorithm (CEAM-CP) of cooperative evolutionary algorithm with multiple populations (CEAM) and constraint programming (CP) is proposed. Specifically, the CEAM-CP algorithm is comprised of two main stages. In the first stage, CEAM is used based on three-layer encoding and full active decoding. Moreover, CEAM has three populations, each of which corresponds to one layer encoding and determines one sub-problem. Moreover, each population evolves cooperatively by multiple cross operations. To further improve the solution quality obtained by CEAM, CP is adopted in the second stage. Experiments are conducted on 13 benchmark instances to assess the effectiveness of multiple crossover operations, CP, and CEAM-CP. Most importantly, the proposed CEAM-CP improves 9 best-known solutions out of 13 benchmark instances.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"5 3","pages":"236-251"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10969581","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896787","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: 0