Computers & Industrial Engineering最新文献_第4页

Collaborative supervision of dangerous goods supply chain: A blockchain-based conceptual platform

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110818

Ao Wang , Guojun Zhu , Jian Li

Effective supervision and the prevention of concealment and false reporting in dangerous supply chain goods require collaboration among multiple departments. Because of its decentralized consensus mechanism, blockchain has potential as an efficient tool for the collaborative supervision of dangerous goods supply chains. In this study, a blockchain-based conceptual platform was proposed for the supervision of dangerous goods supply chains. It features multiple layers, namely, blockchain, storage, interaction, and interface, each fulfilling distinct roles to ensure a comprehensive and efficient system. To enable efficient on-chain data sharing of diverse types of data, three modes of on-chain data integration leveraging IPFS (InterPlanetary File System) and FISCO BCOS were implemented. Additionally, a traceable state machine was proposed, which uses smart contracts to facilitate the traceability of the supervision process. The feasibility of the conceptual platform was validated through the deployment of a prototype platform with eight blockchain nodes. The results indicate that the platform has a latency of 500–550 ms and approximately 2 TPS (Transactions Per Second) to complete data sharing. It also has a latency of less than 3 s and more than 1 TPS when carrying out complex supervision process tracing. The proposed conceptual platform has the ability to address data silo issues in the dangerous goods supply chain. Moreover, the traceability of the supervision process enhances the accurate tracing of accident liabilities.

对危险供应链货物进行有效监管，防止瞒报和谎报，需要多个部门的协作。区块链因其去中心化的共识机制，有望成为危险品供应链协同监管的有效工具。本研究提出了一个基于区块链的危险品供应链监管概念平台。该平台具有多个层次，即区块链、存储、交互和接口，每个层次都发挥着不同的作用，以确保系统的全面性和高效性。为了实现各种类型数据的高效链上数据共享，利用 IPFS（跨行星文件系统）和 FISCO BCOS 实现了三种链上数据集成模式。此外，还提出了一种可追溯状态机，利用智能合约促进监管过程的可追溯性。通过部署带有八个区块链节点的原型平台，验证了概念平台的可行性。结果表明，该平台完成数据共享的延迟时间为 500-550 毫秒，每秒交易量约为 2 TPS。在进行复杂的监管流程追踪时，其延迟时间也小于 3 秒，超过 1 TPS。拟议的概念平台有能力解决危险品供应链中的数据孤岛问题。此外，监管过程的可追溯性也提高了事故责任追查的准确性。

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引用次数: 0

Joint optimization of storage assignment and order batching in robotic mobile fulfillment system with dynamic storage depth and surplus items 具有动态存储深度和剩余物品的机器人移动履约系统中存储分配和订单分批的联合优化

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110767

Zhi Liu , Jiansha Lu , Chenhao Ren , Jun Chen , Zhilong Xu , Guoli Zhao

This paper studies the joint optimization of storage location assignment and order batching in robotic mobile fulfillment systems (RMFS), considering dynamic storage depth and surplus items. Firstly, a joint optimization model of storage location assignment and order batching is established. The model is divided into two stages. The first stage is the item location assignment optimization model, which is used to describe the types and quantities of items placed in each slot on each pod. The second stage is the joint optimization model of pod location assignment and order batching, which is used to describe the coordinates of each pod, the number of order batches, and the order combinations contained in each batch. Considering the vast solution space and the numerous constraints of the constructed model, a two-stage greedy variable neighborhood simulated annealing algorithm (TGVNSA) is introduced to address these challenges. Finally, numerical experiments prove that the algorithm can effectively solve the established model. TGVNSA is evaluated against two conventional methods: variable neighborhood search and adaptive genetic algorithms, focusing on metrics such as pod retrieval times, comprehensive picking costs, CPU time, and CQ value (comprehensive quality in the item location assignment). The findings demonstrate that TGVNSA boasts superior comprehensive performance. Compared with other commonly used strategies in the field such as random, classification, and optimal relevance, the method proposed in this paper demonstrates superior optimization performance, particularly when considering dynamic storage depth and surplus items. Moreover, this paper also proves that, under the same combination of strategies, the joint optimization method proposed in this paper reduces the comprehensive picking costs by 11.46% compared to the separate optimization approach.

本文研究了机器人移动履约系统（RMFS）中存储位置分配和订单分批的联合优化，并考虑了动态存储深度和剩余物品。首先，建立了存储位置分配和订单批量的联合优化模型。该模型分为两个阶段。第一阶段是物品位置分配优化模型，用于描述放置在每个 pod 上每个插槽中的物品类型和数量。第二阶段是吊舱位置分配和订单批次的联合优化模型，用于描述每个吊舱的坐标、订单批次的数量以及每个批次所包含的订单组合。考虑到所建模型的求解空间巨大、约束条件繁多，引入了两阶段贪婪可变邻域模拟退火算法（TGVNSA）来解决这些难题。最后，数值实验证明该算法能有效地解决所建立的模型。针对两种传统方法：可变邻域搜索和自适应遗传算法，对 TGVNSA 进行了评估，重点关注 pod 检索时间、综合拣选成本、CPU 时间和 CQ 值（物品位置分配的综合质量）等指标。研究结果表明，TGVNSA 具有卓越的综合性能。与该领域其他常用策略（如随机、分类和最佳相关性）相比，本文提出的方法表现出更优越的优化性能，特别是在考虑动态存储深度和剩余物品时。此外，本文还证明，在相同的策略组合下，本文提出的联合优化方法比单独优化方法降低了 11.46% 的综合拣选成本。

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引用次数: 0

Assembly line rebalancing problem with human-robot collaboration and a hyper-matheuristic solution approach

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110795

Aslihan Karas Celik, Feristah Ozcelik

In the context of the Industry 5.0 vision, which emphasises the importance of human-centred industries, assembly lines wherein humans and robots work together have emerged as innovative systems that allow the advantages of both to be combined. Accordingly, industrial managers are attempting to implement collaborative systems that will benefit from the consistency of robots and their capacity to work in hazardous environments, as well as the insight and adaptability of humans. Nevertheless, the process of eliminating an existing system and building another one from scratch is both costly and time-consuming. Rather than constructing an entirely new system, it is possible to reconfigure the line based on the new situation, thus enabling the system to adapt to changes. To the best of our knowledge, studies in the literature on collaborative assembly lines have focused on the initial installation phase, while the researchers who have dealt with the rebalancing process have not taken into account the change in the workforce structure as a reason for rebalancing. This study introduces the Assembly Line Rebalancing Problem with Human-Robot Collaboration as a means of filling the perceived gap in the literature. The considered problem addresses the need for line rebalancing to integrate traditional and collaborative robots as operators in existing manual assembly lines. In order to tackle this problem, a mathematical modelling approach and an artificial bee colony algorithm-based hyper-matheuristic algorithm are presented with the objective of optimising cycle time. The results of the computational tests on benchmark problems adapted from the literature demonstrate that the proposed algorithm outperforms the mathematical modelling approach and basic artificial bee colony algorithm.

工业 5.0 的愿景强调以人为本的工业，在这一背景下，人与机器人协同工作的装配线已成为一种创新系统，可将两者的优势结合起来。因此，工业管理者正试图实施协作系统，以利用机器人的一致性及其在危险环境中工作的能力，以及人类的洞察力和适应性。然而，淘汰现有系统并从头开始构建另一个系统的过程既昂贵又耗时。与其建造一个全新的系统，不如根据新情况重新配置生产线，从而使系统能够适应变化。据我们所知，有关协作式装配线的文献研究主要集中在初始安装阶段，而涉及重新平衡过程的研究人员并未将劳动力结构的变化作为重新平衡的原因加以考虑。本研究提出了 "人机协作装配线再平衡问题"，以填补文献中的空白。所考虑的问题涉及生产线再平衡的需求，以整合传统和协作机器人作为现有人工装配线的操作员。为了解决这个问题，提出了一种数学建模方法和基于人工蜂群算法的超智能算法，目的是优化周期时间。对文献中的基准问题进行的计算测试结果表明，所提出的算法优于数学建模方法和基本的人工蜂群算法。

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引用次数: 0

Product tracing or component tracing? Blockchain adoption in a two-echelon supply chain management

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110789

Ardavan Babaei , Majid Khedmati , Mohammad Reza Akbari Jokar , Erfan Babaee Tirkolaee

Consumer awareness of product authenticity and carbon footprint tracing are among the most remarkable reasons for adopting blockchain in the supply chain in today’s world. However, the research literature has not yet examined specific ways to adopt blockchain in the supply chain. This study aims to develop a decision support tool to deal with the adoption of blockchain technology to design a two-echelon supply chain. In this regard, four specific cases for integrating supply chain and blockchain are developed based on types of tracing and block generation authority. In product tracing, green products are investigated throughout the supply chain, while in component tracing, green products are examined between the components of the supply chain. As it is necessary to record and verify the supply chain information by authorities in the blockchain network, in this work, such authorities are taken into account for both links and members of the supply chain. As far as we know, this is the first attempt to classify the various methods of adopting blockchain in Green Supply Chain Management (GSCM) and propose mathematical optimization models related to them. In this line, four Mixed-Integer Linear Programming (MILP) models with the aim of minimizing the costs related to the physical supply chain and blockchain deployment are developed for the integration of the supply chain with blockchain technology. They are treated by the Branch and Efficiency (B&E) algorithm and Simultaneous Data Envelopment Analysis (SDEA) model considering common (cost and service) and innovative (blockchain) criteria. The results showed that link-based and component tracing models are cost-effective. In addition, the cost objective function of green product tracing is more sensitive to the number of blocks than that of component tracing. Eventually, the study provides great opportunities for decision-makers and managers to understand how to adopt blockchain in terms of supply chain network characteristics, cost, transparency, and service.

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引用次数: 0

Maximizing sales: The art of short video creation in livestream e-commerce

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110824

Tong-Yuan Wang , Yi Chen , Zhen-Song Chen , Muhammet Deveci , Dursun Delen

Livestream e-commerce has experienced significant growth in recent years. However, with the intensification of competition, the problem of inadequate exploration of consumer demands has become increasingly prominent and important, which puts key opinion leaders (KOLs) at a disadvantage when cooperating with brand-owners. To tackle this issue, many KOLs have begun using high-quality short videos to provide detailed product information, establish consumer trust, and sell products through live streaming, which is defined as the “short video + livestream” marketing strategy. In this paper, we examine the added value of short video content for consumers and the resulting traffic revenue for KOLs. Furthermore, a game-theoretic model is developed to demonstrate the impact of the “short video + livestream” marketing strategy on the selection of selling modes in livestream e-commerce. The results show that brand-owners and KOLs can benefit from either mode and achieve a mutually beneficial outcome under certain conditions. Moreover, we observe that the brand-owner can be better off in the agency selling mode when the commission rate is low, while the KOL’s preference shifts from the wholesale mode to the commission mode and then back to the wholesale mode with the commission rate increases. Finally, we further examine the value of the “short video + livestream” marketing strategy for both the brand-owner and the KOL.

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引用次数: 0

Dynamic analysis and application of data-driven green behavior propagation on heterogeneous networks

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110822

Linhe Zhu , Bingxin Li

Clear waters and lush mountains constitute invaluable assets, and the sustainable development of the energy economy relies on green behavior. This paper establishes a Centrist–Positive–Negative system for the propagation of green behavior on heterogeneous networks by considering the transition mechanisms among individuals with different attitudes. The equilibrium points of the system are computed, and the sufficient and necessary conditions for positive equilibrium points are provided. We analyze the necessary conditions for Turing instability and the first-order conditions for parameter identification based on optimal control. Numerical simulation results indicate that various network structures can influence the timing of Turing bifurcation. Moreover, the presence of heterogeneity within networks exacerbates the instability of solutions. Media publicity and government management notably exert an inverted U-shaped influence on outcomes. Furthermore, the homogeneity or heterogeneity of the networks should not affect the effectiveness of parameter identification. Utilizing accurate data from the Policy Research Center for Environment and Economy and the China National Environmental Monitoring Centre, we conduct parameter identification on the effectiveness of government management in 13 cities in Jiangsu Province in 2021, yielding promising results. Upon comparison of three time series forecasting models, the LSTM model demonstrates superior performance. A parameter identifying the effectiveness of government management through the prediction of comprehensive air quality indices by using LSTM neural networks yields similarly favorable outcomes. Extending the network to a larger scale further enhances identification performance.

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引用次数: 0

The impact of natural disasters on agricultural credit risk: A theoretical model and empirical test

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110846

Qianting Ma , Weizhong Wang , Ruiqi Leng , Muhammet Deveci , Renjia Liu , Dursun Delen

Natural disasters exert a profound influence on agricultural production and the stable development of rural financial systems. This paper utilizes a multi-agent modeling approach to construct a theoretical framework for understanding the transmission of agricultural credit risk in the context of natural disasters, and empirically examines the underlying mechanisms. The findings reveal several key insights. First, natural disasters significantly escalate credit risk in the agricultural sector. Second, the maturity of agricultural insurance infrastructure plays a critical role in mitigating the impact of natural disasters on agricultural credit risk. Finally, a well-developed agricultural insurance system is essential for mitigating the adverse effects of natural disasters on agricultural credit risk. These findings suggest that accelerating the development of agricultural insurance, particularly in regions prone to natural disasters, could serve as an effective strategy for managing and containing agricultural credit risk.

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引用次数: 0

Spatial multi-attribute decision making: An axiomatic incomplete preference information coverage model 空间多属性决策：公理不完全偏好信息覆盖模型

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110764

Quanbo Zha, Yueying Ren, Jiaxuan Han, Jianping Gu

In addressing the spatial multi-attribute decision making with conflicting incomplete preference information, this study presents an axiomatic preference information coverage model, which can determine the group’s collective stance without distorting individual’s original spatial preferences. First, with a Preference Information (PI) set to encapsulate the incomplete spatial preference information, we extend existing additive spatial value function with a stochastic weight space to assign utilities to alternatives. Dominance relations among pairwise alternatives based on expected utility maximization inform the alternatives priority sequences. Within this context, a novel preference information measure is introduced, serving as the basis for defining the coverage degree associated with alternatives priority sequences relative to the PI. In alignment with the axiomatic foundations governing coverage degree and the principle of maximizing this metric, a dominant rule is formulated to dictate the hierarchy among alternatives priority sequences. The model’s applicability is demonstrated via a numerical example, followed by simulation analyses that probe the influence of different PIs on coverage degree.

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引用次数: 0

A consensus-based multi-criteria decision making method integrating GLDS method and quantum probability theory for risk analysis of human errors 整合 GLDS 方法和量子概率论的基于共识的多标准决策方法，用于人为失误的风险分析

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110847

Qiaohong Zheng , Xinwang Liu

Human error is one of the major contributors to adverse events in a socio-technical system. Human factor analysis and classification system (HFACS), a qualitative method, is widely recognized for analyzing human errors from a systematic perspective. To overcome its limitation in quantitative analysis of the risk of human error, many multi-criteria decision making (MCDM) techniques are combined with HFACS. However, most existing MCDM technique-based HFACS methods ignore the uncertainty of experts’ opinions, the consensus among experts, and the interference effect between experts. To this end, a consensus reaching process (CRP)-based linguistic MCDM integrating the gained and lost dominance score (GLDS) method and quantum probability theory (QPT) is proposed to rank human errors’ risk under the HFACS framework. First, 2-tuple linguistic variables are utilized to represent experts’ opinions on human errors’ risk, which can handle experts’ linguistic opinions in an interpretable, accurate, and simple way. Second, a two-stage feedback mechanism-based CRP shifts to identify the human errors whose risk evaluation information is with low consensus degree and improve their consensus, which contributes to high consensus on human errors’ risk prioritization results. Then, GLDS and QPT are combined to derive human errors’ collective risk value, where GLDS considers both the comprehensive and worst performances of human errors and QPT considers the interference effect among experts. Finally, a case study of risk analysis for human errors involved in hospital care is conducted to show the efficiency of the proposed method.

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引用次数: 0

Some new real-time monitoring schemes for Gumbel’s bivariate exponential time between the events 针对 Gumbel 双变量指数事件间隔时间的一些新的实时监测方案

IF 6.7 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Industrial Engineering

Pub Date : 2025-02-01 DOI: 10.1016/j.cie.2024.110759

Peile Chen , Amitava Mukherjee , Wei Yang , Jiujun Zhang

Monitoring the vector of times between multiple events is essential in a high-quality process such as healthcare operations. To this end, the multivariate time between events (TBE) process monitoring schemes are regularly used as one of the most straightforward and appealing visual tools. The existing literature on multivariate TBE schemes focuses almost exclusively on using complete information availed in vector-based TBE data, often making delayed monitoring as it requires observing the complete set of time values in a vector-valued observation. To address this issue, we recommend monitoring the minimum time value of vector TBE data to reach decisions faster and more efficiently. We introduce several new real-time exponentially weighted moving average (EWMA) schemes for monitoring Gumbel’s bivariate exponential TBE processes. We compare them with existing schemes using fully observed vector-based schemes. A Markov chain method is developed to compute the average time to signal (ATS), and the optimal parameters are found. Finally, three real-life examples are used to illustrate the implementation of the proposed schemes.

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引用次数: 0