Computers & Industrial Engineering最新文献

LLM-enhanced idea generation: data-driven morphological analysis with LDA and NuNER 法学硕士增强的创意生成：使用LDA和NuNER进行数据驱动的形态学分析

IF 6.5 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-31 DOI: 10.1016/j.cie.2025.111426

Jihyun Park , Youngjung Geum

{"title":"LLM-enhanced idea generation: data-driven morphological analysis with LDA and NuNER","authors":"Jihyun Park , Youngjung Geum","doi":"10.1016/j.cie.2025.111426","DOIUrl":"10.1016/j.cie.2025.111426","url":null,"abstract":"<div><div>Technology opportunity discovery (TOD) plays a critical role in firms’ success, leading to extensive research on methodologies for identifying promising technologies. Morphological analysis has been regarded as a prominent method for this purpose, as it systematically derives innovative ideas through creative combinations. However, most previous studies have relied on subjective approaches. Although some analytical and data-driven approaches have been attempted, limited research has addressed how to systematically extract relevant information from large-scale data and how to construct a data-driven morphological matrix using advanced methods such as large language models (LLMs). In response, this study proposes a data-driven approach to morphological analysis for discovering technological opportunities by leveraging LLM-based models to support decision making. Specifically, Latent Dirichlet Allocation (LDA) is used for dimension extraction, and NuNER is applied for value extraction. To evaluate the effectiveness of the proposed framework, a case study was conducted in the context of smart TVs. The results demonstrate that a systematic morphological matrix can be constructed and utilized based on patent data. This approach enables companies to explore innovative ideas through various combinations within the morphological matrix, thereby facilitating the discovery of technological opportunities.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111426"},"PeriodicalIF":6.5,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757913","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 iterated local search based approach for a real rich vehicle routing problem with time windows 一种基于迭代局部搜索的时间窗富车辆路径问题求解方法

IF 6.5 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-30 DOI: 10.1016/j.cie.2025.111422

Andrés Felipe Romero Silva , Alejandra Tabares Pozos , David Alvarez Martinez , John Willmer Escobar

{"title":"An iterated local search based approach for a real rich vehicle routing problem with time windows","authors":"Andrés Felipe Romero Silva , Alejandra Tabares Pozos , David Alvarez Martinez , John Willmer Escobar","doi":"10.1016/j.cie.2025.111422","DOIUrl":"10.1016/j.cie.2025.111422","url":null,"abstract":"<div><div>The vehicle routing problem with multiple real constraints is one of the leading logistics challenges for technology-based companies. Despite being a classic and well-studied real-world routing problem, only a few companies have implemented algorithms to solve it entirely and automatically. Based on a real case study of a technology-based company, this paper proposes a solution to an asymmetric close-open mixed vehicle routing problem that considers capacity constraints, heterogeneous fleet, time windows, and computational and operational implementation constraints. A hybrid algorithm is proposed, which combines an iterative local search strategy with a set-partitioning problem strategy, utilizing a computing architecture that meets all the constraints to solve the considered problem. Benchmarking was conducted using classic instances from the literature and actual instances from the company to demonstrate the performance of the proposed methodology. The solutions for the companýs instances have an average gap of 9% compared with the upper bound obtained via the related knapsack problem. In contrast, the results for classical instances have an average gap of 8% compared with the best-found solution in the literature. Moreover, the algorithm and the architecture created are already used in the company’s day-to-day operations, validating the efficiency and effectiveness of the proposed work.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111422"},"PeriodicalIF":6.5,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750398","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

A dynamic approach to predict systems requirements for continuous improvement 预测系统需求的动态方法，以便持续改进

IF 6.5 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-30 DOI: 10.1016/j.cie.2025.111415

Nicola Epicoco, Alessandro Massaro

{"title":"A dynamic approach to predict systems requirements for continuous improvement","authors":"Nicola Epicoco, Alessandro Massaro","doi":"10.1016/j.cie.2025.111415","DOIUrl":"10.1016/j.cie.2025.111415","url":null,"abstract":"<div><div>This paper proposes a technique to predict the system requirements (i.e., determine the proper input values) to ensure a continuous improvement of dynamic systems. The method makes use of the Data Envelopment Analysis technique to determine the efficiency of the considered system, whose dynamics is modeled through a state-space representation. To take into account the uncertainty on their values and the presence of possible disturbances, future state variables and outputs are modeled as fuzzy numbers, while system inputs are represented as stochastic variables with suitable distributions. A Monte Carlo simulation is applied by varying at each iteration the input parameters to identify the highest efficiency value (and the corresponding inputs), thus ensuring the robustness of the approach. The iterative application of the method ensures the continuous improvement of the system performance at each time period, up to the maximum efficiency value allowed by the available resources, then guaranteeing its maintenance over time. Thanks to its generality, the method represents a useful tool for decision-makers to plan future actions and evaluate the impact of decisions. An illustrative example and a real case study (characterized by a high efficiency) on a Supply Chain Network producing surgical face masks are presented to show the effectiveness of the proposed approach, whose outcomes are compared against several commonly adopted predictive analysis techniques.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111415"},"PeriodicalIF":6.5,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750390","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

Digital twin optimization: A sequential approach 数字孪生优化：顺序方法

IF 6.5 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-29 DOI: 10.1016/j.cie.2025.111235

Xueru Zhang , Dennis K.J. Lin , Lin Wang

{"title":"Digital twin optimization: A sequential approach","authors":"Xueru Zhang , Dennis K.J. Lin , Lin Wang","doi":"10.1016/j.cie.2025.111235","DOIUrl":"10.1016/j.cie.2025.111235","url":null,"abstract":"<div><div>As a virtual counterpart of physical systems, the digital twin is an advanced technology that has gained significant importance across various industries due to its numerous benefits and wide-ranging applications. However, optimizing digital twins presents a complex challenge, particularly when dealing with multiple responses. This complexity arises from the intricate computational processes required to identify optimal inputs, which can hinder timely decision-making. In this paper, we propose an approach that transforms multi-objective optimization into a single-objective optimization problem and subsequently applies sequential optimization to the single objective. Our method integrates sequential data collection with digital twin learning techniques, encompassing four key steps: data collection, evaluation, optimization, and decision-making. The effectiveness of the proposed approach is demonstrated through three case studies, highlighting its capability to optimize multi-response digital twins. The simplicity of implementation and remarkable adaptability of this approach make it a powerful tool for capturing and representing the intricate nuances of digital twins. This enhanced digital twin facilitates a deeper understanding of the underlying physical system, ultimately accelerating the optimization of its performance.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111235"},"PeriodicalIF":6.5,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750397","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

Transforming urban freight transportation: Service network design for synergy with passenger transportation in transit systems 改造城市货运：与客运系统协同的服务网络设计

IF 6.5 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-28 DOI: 10.1016/j.cie.2025.111405

Jie Lin, Fangni Zhang

{"title":"Transforming urban freight transportation: Service network design for synergy with passenger transportation in transit systems","authors":"Jie Lin, Fangni Zhang","doi":"10.1016/j.cie.2025.111405","DOIUrl":"10.1016/j.cie.2025.111405","url":null,"abstract":"<div><div>The increasing popularity of online shopping and the resulting surge in parcel volumes are exerting significant pressure on urban logistics systems. To address this challenge, a novel solution known as “urban co-modality” has emerged, which promotes collaborative transportation between freight and passengers. This study examines the service network design for urban co-modality, which synergizes passenger and freight transportation by leveraging the spare capacity of urban bus systems. In contrast to traditional freight transportation systems, co-modal systems enable freight demands to be fulfilled through a combination of trucking and bus transportation, in addition to trucking alone. Designated bus stops and terminals can serve as freight transfer points. Using a time–space network as the modeling framework, we propose an arc-based formulation that simultaneously addresses truck fleet sizing, routing, and scheduling, as well as freight allocation, with the objective of minimizing total operating costs. A column generation-based two-stage method is developed to efficiently solve the problem. Extensive numerical experiments demonstrate that the two-stage method outperforms both Gurobi and a column generation-based heuristic. Our results indicate that urban co-modality can lead to an average reduction of 27% in operating costs and a 37% reduction in total truck mileage, considering varying freight volumes in a real-world case study. Furthermore, we examine the impact of freight volume, collaboration between bus service providers and logistics providers, and the selection of transfer locations on the efficiency of the co-modality system. These findings provide a foundation and reference for assessing the benefits of co-modality patterns, developing operational strategies, and guiding policy formulation for co-modality systems.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111405"},"PeriodicalIF":6.5,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144738250","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

Data-driven optimization strategy of raw material procurement under uncertainties of price fluctuations and production demand in industrial enterprises 价格波动和生产需求不确定性下工业企业原材料采购数据驱动优化策略

IF 6.5 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-27 DOI: 10.1016/j.cie.2025.111425

Jiang Luo, Yalin Wang, Chenliang Liu, Guohua Wu, Weihua Gui

{"title":"Data-driven optimization strategy of raw material procurement under uncertainties of price fluctuations and production demand in industrial enterprises","authors":"Jiang Luo, Yalin Wang, Chenliang Liu, Guohua Wu, Weihua Gui","doi":"10.1016/j.cie.2025.111425","DOIUrl":"10.1016/j.cie.2025.111425","url":null,"abstract":"<div><div>Raw material procurement planning is an important element in the operational decision-making of most industrial enterprises, directly influencing production planning and economic performance. The dynamic fluctuations in market prices and production demand require enterprises to adjust procurement strategies in a timely manner, ensuring reasonable and stable procurement costs as well as the timely supply of raw materials. However, existing methods often assume that prices and production demand follow deterministic distributions when making procurement decisions. To address this, this paper introduces a dynamic replay reinforcement learning (DRRL) strategy, which could adapt to dynamic shifts in market conditions and production demand by selecting the optimal strategy based on the current state. First, a representative long short-term memory network is utilized to capture short-term fluctuations in raw material prices and production demand. Following this, a dynamic raw material procurement framework is established based on the actual procurement processes of process industries. Finally, a Deep Q-Network method with a dynamic time-aligned experience replay mechanism is designed to make sequential decisions on procurement quantities for each cycle. The effectiveness of the proposed method is validated using a real-world raw material coal procurement optimization dataset from an industrial enterprise.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111425"},"PeriodicalIF":6.5,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750396","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

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

Internal mechanism of resource allocation efficiency and profit level in supply chain alliance: New evaluation, classification and adjustment methods 供应链联盟资源配置效率与利润水平的内在机制：新的评价、分类与调整方法

IF 6.5 1区工程技术

Computers & Industrial Engineering Pub Date : 2025-07-24 DOI: 10.1016/j.cie.2025.111420

Xu Guo, Lei Chen

{"title":"Internal mechanism of resource allocation efficiency and profit level in supply chain alliance: New evaluation, classification and adjustment methods","authors":"Xu Guo, Lei Chen","doi":"10.1016/j.cie.2025.111420","DOIUrl":"10.1016/j.cie.2025.111420","url":null,"abstract":"<div><div>Supply chain alliance cooperation is of great significance to optimize resource allocation and improve profits, but the impact of resource allocation efficiency on profits has not been quantitatively studied, and the profit loss caused by resource allocation inefficiency has not been attention and improved. Therefore, based on hybrid network DEA, this paper proposes a new method to measure resource allocation efficiency from the perspective of profit, which quantifies the profit loss caused by resource allocation inefficiency for the first time. To reduce profit loss, multi-output and multi-input technical bias method (MMTB) is proposed to guide the rearrangement of upstream and downstream structures in supply chain alliances, so as to accurately find structural rearrangement plan under profit maximization, and then realize the adjustment of profit loss. On this basis, a new classification method of profit loss (adjustable profit loss and unadjusted profit loss) and a new efficiency measurement method (profit adjustable efficiency) are proposed. Finally, we analyze the data of 25 supply chains in resin producing companies to verify our proposed method. The resulting resource allocation inefficiency is compared with the classical method.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"208 ","pages":"Article 111420"},"PeriodicalIF":6.5,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144720936","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