Computers & Industrial Engineering最新文献

Multi-Objective Monarch Butterfly Optimization algorithm for agri-food workflow scheduling in fog–cloud 雾云环境下农业食品工作流调度的多目标帝王蝶优化算法

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-26 DOI: 10.1016/j.cie.2025.111386

Kaya Souaïbou Hawaou , Sonia Yassa , Vivient Corneille Kamla , Laurent Bitjoka , Olivier Romain

{"title":"Multi-Objective Monarch Butterfly Optimization algorithm for agri-food workflow scheduling in fog–cloud","authors":"Kaya Souaïbou Hawaou , Sonia Yassa , Vivient Corneille Kamla , Laurent Bitjoka , Olivier Romain","doi":"10.1016/j.cie.2025.111386","DOIUrl":"10.1016/j.cie.2025.111386","url":null,"abstract":"<div><div>The explosion of data and connected objects has encouraged the development of distributed computing environments such as cloud, fog and edge, facilitating real-time data processing. In the agri-food sector, this evolution is reinforced by the emergence of the Industrial Internet of Things (IIoT) and fog–cloud computing. One of the major challenges of these environments is the efficient scheduling of applications while respecting the SLA principle. This article deals with the <strong>multi-objective optimization</strong> of <strong>agri-food workflow scheduling</strong> using an <strong>improved version of the Monarch Butterfly Optimization (MO-MBO) algorithm</strong>. Our approach integrates <strong>Pareto dominance</strong>, a <strong>greedy strategy</strong>, and a <strong>self-adaptive strategy</strong> to effectively handle four <strong>conflicting objectives</strong>: makespan, cost, energy, and latency. Simulations carried out on FogWorkflowSim for the agri-food health monitoring workflow demonstrate that MO-MBO is energy-efficient (68.63% compared to the genetic algorithm (GA), 67.78% compared to the particle swarm optimization algorithm (PSO), and 85.48% compared to the Non Dominated Sorting Genetic Algorithm-II (NSGA-II)) and improves latency (0.35% for GA, 0.14% for PSO, and 0.10% for NSGA-II). However, cost increases marginally, by 0.85% for GA, 0.29% for PSO, and 0.10% for NSGA-II. Makespan, meanwhile, increases by 31.41% versus GA, 29.27% versus PSO, and 10.67% compared versus NSGA-II. The results highlight the ability of MO-MBO to effectively balance multiple, conflicting objectives, making it a promising solution for <strong>energy-efficient</strong>, <strong>low-latency scheduling</strong> in fog–cloud systems.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111386"},"PeriodicalIF":6.7,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An offline reinforcement learning-based framework for proactive robot assistance in assembly task 基于离线强化学习的机器人主动辅助装配任务框架

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-26 DOI: 10.1016/j.cie.2025.111313

Yingchao You, Boliang Cai, Ze Ji

{"title":"An offline reinforcement learning-based framework for proactive robot assistance in assembly task","authors":"Yingchao You, Boliang Cai, Ze Ji","doi":"10.1016/j.cie.2025.111313","DOIUrl":"10.1016/j.cie.2025.111313","url":null,"abstract":"<div><div>Proactive robot assistance plays a critical role in human–robot collaborative assembly (HRCA), enhancing operational efficiency, product quality and workers’ ergonomics. The shift toward mass personalisation in industries brings significant challenges to the collaborative robot that must quickly adapt to product changes for proactive assistance. State-of-the-art knowledge-based task planners in HRCA struggle to quickly update their knowledge to adapt to the change of new products. Different from conventional methods, this work studies learning proactive assistance by leveraging reinforcement learning (RL) to train a policy, ready to be used for robot proactive assistance planning in HRCA. To address the limitations therein, we propose an offline RL framework where a policy for proactive assistance is trained using the dataset visually extracted from human demonstrations. In particular, an RL algorithm with a conservative Q-value is utilised to train a planning policy in an actor–critic framework with carefully designed state space and reward function. The experimental results show that with only a few demonstrations performed by workers as input, the algorithm can train a policy for proactive assistance in HRCA. The assistance task provided by the robot can fully meet the task requirement and improve human assembly preference satisfaction by 47.06% compared to a static strategy.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111313"},"PeriodicalIF":6.7,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144712855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How to realize sustainable urban water supply network through intelligent governance of leakage: A perspective of water-conservation strategy optimization 如何通过渗漏智能治理实现城市供水网络的可持续发展：一个节水策略优化的视角

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-24 DOI: 10.1016/j.cie.2025.111414

Zhaolin Ouyang , Liying Yu , Ziyuan Zhang

{"title":"How to realize sustainable urban water supply network through intelligent governance of leakage: A perspective of water-conservation strategy optimization","authors":"Zhaolin Ouyang , Liying Yu , Ziyuan Zhang","doi":"10.1016/j.cie.2025.111414","DOIUrl":"10.1016/j.cie.2025.111414","url":null,"abstract":"<div><div>Leakage in urban water supply network is a common issue worldwide, which exacerbates water scarcity. Although water-saving contract provides a novel approach for achieving intelligent leakage control, how to formulate effective water-conservation strategy remains an urgent issue to be solved. Based on this, this paper focuses on the water-conservation service supply chain consisting of a water supply company and a water-conservation service company. Using differential game, this paper constructs dynamic decision-making models for multiple water-conservation modes, compares the differences between different modes and reveals the optimal water-conservation strategy. The results show that leakage control cost coefficient and unit cost of water-conservation services negatively affect the optimal leakage control efforts and leakage control level in urban water supply network, while multiple factors jointly influence the optimal technological innovation efforts. Compared with autonomous water conservation mode, cooperative modes are superior in terms of both profit and water savings when the unit cost of water-conservation services and leakage control cost coefficient are higher. Among three cooperative modes, from the point of profit maximization, cooperating innovation and sharing revenue mode is superior, and appropriate distribution of leakage control cost and water-conservation revenue can contribute to the achievement of this mode. From maximizing water-conservation benefit, sharing innovation-input and water-conservation revenue mode is optimal, and whether members can achieve this mode depends on sharing ratios of the water-conservation revenue and the innovation cost.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111414"},"PeriodicalIF":6.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrating digital assistant with human operators for realizing process monitoring in manual machine tool operations 将数字辅助与人工操作相结合，实现手动机床操作过程监控

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-24 DOI: 10.1016/j.cie.2025.111421

Sunidhi Dayam, K.A. Desai

{"title":"Integrating digital assistant with human operators for realizing process monitoring in manual machine tool operations","authors":"Sunidhi Dayam, K.A. Desai","doi":"10.1016/j.cie.2025.111421","DOIUrl":"10.1016/j.cie.2025.111421","url":null,"abstract":"<div><div>The human skill sets are critical in monitoring and identifying in-process faults during manual machine operations. The shortage of skilled human operators, lack of consistency in decision-making, and slower response result in lower productivity and part quality. This paper presents the digital assistant as a decision support system to improve operators’ perceptions about tool wear state and chatter onset while running the manually operated machines. The digital assistant acquires real-time process information using Acoustic Emission and Accelerometer sensors integrated with the data acquisition elements. The tool wear and chatter information is extracted from the sensor data using a decision-making module combining Root Mean Square and Support Vector Machine (SVM) with a quadratic kernel. The SVM classifier is trained using a learning-through-demonstration approach to digitize the expertise of a skilled operator. The decision-making module is integrated with the Human Machine Interface (HMI) unit to display real-time process information for appraising machine operators. The prediction abilities of the digital assistant are corroborated by performing machining experiments for different tool-work material combinations on the conventional manually operated engine lathe. The studies showed that the digital assistant can effectively capture process fault information and complement the decision-making abilities of human operators.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111421"},"PeriodicalIF":6.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint multi-objective optimization of maritime SAR equipment deployment using high-risk area recognition and SA-APSO 基于高风险区域识别和SA-APSO的海上SAR装备联合多目标优化部署

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-24 DOI: 10.1016/j.cie.2025.111399

Yaxin Dong , Hongxiang Ren , Rui Tao , Jian Sun , Yi Zhou

{"title":"Joint multi-objective optimization of maritime SAR equipment deployment using high-risk area recognition and SA-APSO","authors":"Yaxin Dong , Hongxiang Ren , Rui Tao , Jian Sun , Yi Zhou","doi":"10.1016/j.cie.2025.111399","DOIUrl":"10.1016/j.cie.2025.111399","url":null,"abstract":"<div><div>Pre-positioning of search and rescue (SAR) equipment is a practical approach for rapidly and effectively responding to maritime emergencies. In this study, we present a comprehensive method to optimize the location and configuration of SAR equipment (LCSRE), which are critical determinants of emergency response efficiency. First, we use a random forest (RF) model to identify high-risk subareas based on maritime accident data and Automatic Identification System (AIS) data, providing a data-driven foundation for informed LCSRE decisions. Next, the Fuzzy Comprehensive Evaluation Method (FCEM) is employed to calculate a comprehensive impact index for external interference factors at candidate sites, quantifying their suitability. Finally, considering the supportive role of islands, we develop a model aimed at minimizing response times and overall configuration costs while improving service coverage. To solve the model, we propose a Simulated Annealing-enhanced Adaptive Particle Swarm Optimization (SA-APSO) algorithm. The numerical experiments demonstrate that the proposed method achieves an average cost reduction of 69.2% and a coverage improvement of 30.1% compared to the ship-only strategy. Moreover, by integrating the high-risk subarea recognition into multimodal deployment planning, it further reduces total cost by an additional 3.49%–18.36% and increases coverage by 5.23%–11.33% relative to a risk-neutral multimodal baseline. Compare to the actual 2024 configuration plan, the optimized solution increases coverage from 85.47% to 95.41% and reduces total cost by 11.63%. These results demonstrate the practical value and robustness of the proposed method for maritime SAR planning.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111399"},"PeriodicalIF":6.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Scalable ride-matching and dispatching model for shared autonomous electric vehicles with real-time demand prediction 基于实时需求预测的共享型自动驾驶汽车可扩展出行匹配与调度模型

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-24 DOI: 10.1016/j.cie.2025.111419

Ning Wang , Kai Shang , Hangqi Tian , Yuntao Guo

{"title":"Scalable ride-matching and dispatching model for shared autonomous electric vehicles with real-time demand prediction","authors":"Ning Wang , Kai Shang , Hangqi Tian , Yuntao Guo","doi":"10.1016/j.cie.2025.111419","DOIUrl":"10.1016/j.cie.2025.111419","url":null,"abstract":"<div><div>Shared Autonomous Electric Vehicles (SAEVs) hold significant potential for reducing travel costs and alleviating traffic congestion. However, existing SAEV dispatch algorithms often employ shortsighted strategies and suffer from high computational complexity. This paper proposes a hierarchical framework for dynamic ride-matching and fleet dispatching that unifies demand forecasting and real-time decision-making. At the lower level, a high-precision passenger demand prediction model is constructed using an attention-based spatial–temporal graph convolutional network, leveraging hexagonal grid partitioning and historical travel data to generate fine-grained, time-sensitive forecasts. Building on these predictive insights, the upper-level decision module models the ride-matching task as a Markov decision process and synergizes this information within a multi-agent reinforcement learning framework, solved using an improved Double Deep Q-Network (Double DQN) algorithm. Experiments using real-world travel data from Chengdu in a multi-agent simulation environment demonstrate the effectiveness of the integrated framework. Results show that the demand prediction model achieves a root mean square error of 1.046, and the ride-matching decision method completes 93.76% of travel orders with only 76.6% of the SAEV fleet, significantly improving vehicle utilization. Additionally, when enabling both ride-sharing and demand-aware dispatching, as opposed to operating without these functionalities, the model achieves a 15% higher order completion rate. These results underscore the framework’s ability to couple high-fidelity forecasting with scalable decision-making, offering a robust and adaptive solution for SAEV-based urban mobility systems.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111419"},"PeriodicalIF":6.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pricing and green investment of technology-differentiated manufacturers under blockchain technology 区块链技术下技术差异化制造商定价与绿色投资

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-23 DOI: 10.1016/j.cie.2025.111418

Susu Cheng , Dongdong Li , Tiantian Liu

{"title":"Pricing and green investment of technology-differentiated manufacturers under blockchain technology","authors":"Susu Cheng , Dongdong Li , Tiantian Liu","doi":"10.1016/j.cie.2025.111418","DOIUrl":"10.1016/j.cie.2025.111418","url":null,"abstract":"<div><div>Green products are gaining increasing interest from consumers, but they are often uncertain about the green attributes of products. Although blockchain technology has emerged as a transformative tool for enhancing product traceability and transparency, the adoption of blockchain technology exhibits pronounced heterogeneity among manufacturers with divergent technological capabilities. Additionally, consumers’ behavioral characteristics significantly influence whether manufacturers adopt blockchain technology. This paper segments consumers into blockchain-sensitive and blockchain-insensitive consumers, develops a duopoly game model of technology-differentiated manufacturers’ product pricing and green investment under blockchain technology, explores the conditions for different types of manufacturers to adopt blockchain, and examines how different adoption scenarios impact manufacturers’ decisions. Results show that: (i) Under different blockchain adoption modes, the proportion of blockchain-sensitive consumers or the reservation price discount rate has different impacts on manufacturers’ pricing and green investment decisions. (ii) The manufacturer adopting blockchain will increase the retail price, but whether increase green R&D levels depends on the unit information collection cost. (iii) The technologically advantaged manufacturer always adopts blockchain, while the technologically disadvantaged manufacturer tends to adopt blockchain only when the technological gap is small, and this tendency is inversely related to the unit information collection cost.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111418"},"PeriodicalIF":6.7,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The professional driver training timetabling problem: MILP formulations and efficient heuristic 职业驾驶训练排课问题：MILP公式与有效启发式

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-23 DOI: 10.1016/j.cie.2025.111396

Mohammed Bazirha

{"title":"The professional driver training timetabling problem: MILP formulations and efficient heuristic","authors":"Mohammed Bazirha","doi":"10.1016/j.cie.2025.111396","DOIUrl":"10.1016/j.cie.2025.111396","url":null,"abstract":"<div><div>According to the Moroccan Road Code 52.05, drivers involved in the transport of goods and passengers must obtain a professional card, which is issued only after completing training at accredited centers. Motivated by the challenges faced by these centers, this study, the first of its kind, focuses on modeling and solving the professional driver training timetabling problem. Its main challenge is ensuring that each group adheres to the theoretical course duration. When a group is in practice, it misses some theoretical sessions. As a result, the decision-maker must ensure that groups assigned to the same room during a given period receive an equal duration of training to prevent overlap. Mixed integer linear programming (MILP) models are proposed to optimize the use of limited resources, such as trainers, rooms, and vehicles, while complying with all constraints specified in the decree governing professional driver training. A simulation is conducted with a variable number of training groups to identify the optimal allocation of resources. The proposed MILP models meet the current needs of these centers but fail to generate feasible schedules within a reasonable time as demand and resources increase. To overcome the scalability issue, a simulated annealing (SA)-based heuristic is proposed, which uses Shift and Swap moves to explore the search space. Constraints and resource allocation are managed by a dedicated algorithm. Computational results show that the number of vehicles and rooms is proportional to that of groups, though the ratio varies by training type. Consequently, decision-makers should identify demand for each training type, allocate resources accordingly, and maximize the number of groups to be trained with available resources.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111396"},"PeriodicalIF":6.7,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mixed-defect wafer map separation and detection based on single-defect wafer map 基于单缺陷晶圆图的混合缺陷晶圆图分离与检测

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-23 DOI: 10.1016/j.cie.2025.111395

Jialin Li , Kun Long , Renxiang Chen , Yuxiong Li , Xianzhen Huang

{"title":"Mixed-defect wafer map separation and detection based on single-defect wafer map","authors":"Jialin Li , Kun Long , Renxiang Chen , Yuxiong Li , Xianzhen Huang","doi":"10.1016/j.cie.2025.111395","DOIUrl":"10.1016/j.cie.2025.111395","url":null,"abstract":"<div><div>The difficulty in labeling wafer maps of mixed-defect has affected the development of deep learning-based detection models. In the case of zero labeled samples, this paper proposes a mixed-defect wafer map separation and detection (MDWMSD) method based on single-defect wafer map. First, mixed-defect wafers are generated using different categories of single-defect wafers. Then, a mixed-defect separation model was proposed based on a residual neural network with U-net structure to separate mixed-defect wafer map into several single-defect wafer maps. Finally, the separated single-defect wafers are identified using the trained single-defect classifier. During the validation process, two mixed-defect wafer map separation models were developed using single-defect wafer maps from the MIR-WM811k dataset and the MixedWM38 dataset, respectively. The developed model was then tested on mixed-defect wafer map in the MixedWM38 dataset. The results show that the detection accuracy of mixed-defect wafer under zero samples condition can reach 95% and 85.38% in two cases, which proves the effectiveness of the proposed method.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111395"},"PeriodicalIF":6.7,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From theory to practice: optimizing makespan in no-wait jobshops with no-passing constraints 从理论到实践：无等待车间无通过约束的最大完工时间优化

IF 6.7 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-20 DOI: 10.1016/j.cie.2025.111402

Shih-Wei Lin , Kuo-Ching Ying

{"title":"From theory to practice: optimizing makespan in no-wait jobshops with no-passing constraints","authors":"Shih-Wei Lin , Kuo-Ching Ying","doi":"10.1016/j.cie.2025.111402","DOIUrl":"10.1016/j.cie.2025.111402","url":null,"abstract":"<div><div>This paper addresses the hitherto unexplored <em>NP</em>-complete problem of minimizing the makespan in no-wait jobshops with no-passing constraints. Motivated by the significant gap in the scheduling literature and practical applications, our study aims to design an efficient and effective matheuristic algorithm that can overcome computational barriers to the optimal solution of this problem. Extensive computational experiments on four benchmark datasets demonstrate that the proposed algorithm consistently yields optimal solutions for problems containing up to 1000 jobs, and efficiently solves ultra-large instances with up to 2000 jobs and 20 machines within a time limit of four hours. These promising results not only validate the effectiveness of the algorithm but also underscore its potential for addressing intricate scheduling challenges with practical relevance. The contributions of this work include the development of a theoretically sound and computationally efficient matheuristic paradigm tailored to a highly challenging scheduling problem, and the advancement of both theoretical understanding and practical applications in industrial settings.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111402"},"PeriodicalIF":6.7,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0