Computers & Industrial Engineering最新文献_第8页

A new mathematical model and meta-heuristic algorithm for order batching, depot selection, and assignment problem with multiple depots and pickers 针对具有多个仓库和拣货员的订单分批、仓库选择和分配问题的新数学模型和元启发式算法

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

Computers & Industrial Engineering

Pub Date : 2024-09-27 DOI: 10.1016/j.cie.2024.110585

The ‘order picking problem’ involves the efficient and organized retrieval of items from shelves to fulfill customer orders. In this study, we consider a new configuration of warehouse system with multiple pickers and depots (m-pickers & n-depots) for manually operated ‘picker-to-parts’ warehouses. The efficiency of the process is measured based on two metrics: i- total order picking distance of each picker ii- total number of pickers assigned to each of depots. The handled problem is called as ‘Order Batching, Depot Selection and Assignment Problem with Multiple Depots and Multiple Pickers (OBDSAPMDMP)¹’. To solve this complex problem, a new bi-objective Mixed-Integer Linear Programming (MILP) formulation for small-sized problems and a meta-heuristic called ‘Dependent Harmony Search (DHS)²’ for large-sized problems are proposed. The performance of DHS algorithm is evaluated by comparing the optimal results attained by MILP model. For the problem size of 10 orders, the average gap (%) in distance between the solution of DHS and MILP is 4.22%, although in some experiments DHS can find the optimal solution in a very short time. Also, in related analysis, it is seen that constructing multiple depots instead of one left-most located depot decreases total order picking distance by 7.11% on average.

订单分拣问题 "涉及从货架上高效、有序地检索物品，以完成客户订单。在本研究中，我们考虑了一种新的仓库系统配置，即手动操作的 "拣货员到零件 "仓库，该系统具有多个拣货员和仓库（m-pickers & n-depots）。该流程的效率根据两个指标来衡量：i- 每个拣货员的总订单拣货距离 ii- 分配给每个仓库的拣货员总数。所处理的问题被称为 "具有多个仓库和多个拣选工的订单分批、仓库选择和分配问题（OBDSAPMDMP）1"。为解决这一复杂问题，我们提出了一种新的双目标混合整数线性规划（MILP）公式来解决小型问题，并提出了一种名为 "依赖和谐搜索（DHS）2 "的元启发式来解决大型问题。通过比较 MILP 模型获得的最优结果，评估了 DHS 算法的性能。在问题规模为 10 阶时，DHS 的解与 MILP 的解之间的平均距离差距（%）为 4.22%，尽管在某些实验中 DHS 可以在很短的时间内找到最优解。此外，在相关分析中还发现，建造多个仓库而不是一个位于最左侧的仓库可使订单分拣总距离平均减少 7.11%。

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引用次数: 0

Analyzing component failures in series-parallel systems with dependent components 分析具有从属组件的串并联系统中的组件故障

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

Computers & Industrial Engineering

Pub Date : 2024-09-27 DOI: 10.1016/j.cie.2024.110604

This paper investigates a series-parallel system comprising

N

independent subsystems with interchangeable dependent components, a prevalent reliability structure in engineering and network design. The primary aim of this research is to derive the joint probability distribution of the number of failed components within these configurations, considering component dependence and varying distributions across subsystems. This approach reflects a more realistic scenario than previously explored in the literature. Initially, the analysis is conducted for systems with two subsystems and subsequently extended to encompass configurations with

N

subsystems. The study also evaluates key reliability metrics including the average number of failed components and the mean time to failure (MTTF) of the entire system, theoretically proving that the system’s MTTF increases with the number of components under certain sufficient conditions. In addition to probabilistic analysis, an optimization problem is addressed to determine the optimal allocation of components within each subsystem. The objective is to minimize the average cost associated with corrective maintenance, thereby enhancing the cost-effectiveness of system operation.

本文研究了由 N 个独立子系统组成的串并联系统，这些子系统具有可互换的从属组件，是工程和网络设计中普遍采用的可靠性结构。这项研究的主要目的是，在考虑到组件依赖性和各子系统间不同分布的情况下，推导出这些配置中故障组件数量的联合概率分布。与之前的文献相比，这种方法反映了一种更为现实的情况。分析最初针对两个子系统的系统进行，随后扩展到包含 N 个子系统的配置。研究还评估了关键的可靠性指标，包括故障组件的平均数量和整个系统的平均故障时间（MTTF），从理论上证明了在某些充分条件下，系统的 MTTF 会随着组件数量的增加而增加。除概率分析外，还需要解决一个优化问题，以确定每个子系统内组件的最佳分配。目标是最大限度地降低与纠正性维护相关的平均成本，从而提高系统运行的成本效益。

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引用次数: 0

A model for remaining useful life interval prediction of servo turret power head system of turn-milling center under time-varying operating conditions 时变工作条件下车削中心伺服转塔动力头系统剩余使用寿命区间预测模型

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

Computers & Industrial Engineering

Pub Date : 2024-09-26 DOI: 10.1016/j.cie.2024.110592

With the diversification of machining tasks in turn-milling centers, the service conditions of the servo turret power head system are complex and changeable, and there are multi-source uncertainties in the degradation monitoring process. Based on the improved conditionally parameterized convolutions and nonlinear Wiener process, this paper proposes an interval prediction model suitable for the remaining useful life (RUL) under time-varying operating conditions. Firstly, a method for making sample performance degradation labels based on operating condition classification is proposed, and the labels under continuously identical operating conditions are linearized according to the classification results of operating conditions to solve the problem of inconsistent degradation rate under time-varying operating conditions. Then, a conditionally parameterized convolutions module considering global–local features (GL-CondConv) is proposed, and the convolution kernel parameters are adaptively learned according to the input samples, so that the model fully considers the influence of the features of each sample on the prediction results under time-varying operating conditions. Finally, the nonlinear Wiener process is used to estimate the RUL interval of the equipment to quantify the RUL uncertainty. The effectiveness of the proposed method is verified on the servo turret power head system dataset and PHM bearing dataset.

随着车铣中心加工任务的多样化，伺服转塔动力头系统的工况复杂多变，在退化监测过程中存在多源不确定性。本文基于改进的条件参数化卷积和非线性维纳过程，提出了一种适用于时变工况下剩余使用寿命（RUL）的区间预测模型。首先，提出了一种基于工况分类的样本性能退化标签制作方法，并根据工况分类结果对连续相同工况下的标签进行线性化处理，以解决时变工况下退化率不一致的问题。然后，提出了考虑全局-局部特征的条件参数化卷积模块（GL-CondConv），根据输入样本自适应学习卷积核参数，使模型充分考虑了时变工况下各样本特征对预测结果的影响。最后，利用非线性维纳过程估计设备的 RUL 间隔，量化 RUL 不确定性。在伺服转塔动力头系统数据集和 PHM 轴承数据集上验证了所提方法的有效性。

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引用次数: 0

Grinding process optimization considering carbon emissions, cost and time based on an improved dung beetle algorithm 基于改进的蜣螂算法，在考虑碳排放、成本和时间的基础上优化研磨工艺

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

Computers & Industrial Engineering

Pub Date : 2024-09-26 DOI: 10.1016/j.cie.2024.110600

During the machining phase, carbon emissions produced by grinding machines account for a significant proportion of the total emissions. Optimizing grinding process parameters is an effective energy-saving measure, which can notably reduce carbon emissions. However, most of the research on parameter optimization related to carbon emissions and energy saving is focused on turning and milling processes, with limited studies on the grinding process. To address this gap, this paper introduces an optimization method for grinding process parameters that considers carbon emissions and seeks to balance emissions, time, and cost in the grinding process. Initially, we quantify the relationship between grinding parameters and optimization objectives and a corresponding multi-objective optimization model is established subsequently. Then an improved multi-objective dung beetle optimization algorithm (INSDBO) is proposed to solve this model. As a case study, we conduct experiments on the machining of a plunger. Simulation results indicate that after optimization, carbon emissions, grinding costs and time have decreased by 11.7%,7.7%, and 6.7% respectively, validating the effectiveness of the proposed optimization method. When compared with the Adaptive Weighted Evolutionary Algorithm (AdaW)、the traditional dung beetle algorithm (NSDBO), and Multi-Stage Multi-Objective Evolutionary Algorithm (MSEA), the improved dung beetle optimization algorithm(INSDBO) showed superior performance. This refined algorithm can suggest optimal parameters in the grinding process, thereby reducing carbon emissions, machining time, and costs.

在机械加工阶段，磨床产生的碳排放量占总排放量的很大比例。优化磨削工艺参数是一种有效的节能措施，可以显著减少碳排放。然而，与碳排放和节能相关的参数优化研究大多集中在车削和铣削过程，对磨削过程的研究十分有限。针对这一空白，本文介绍了一种考虑碳排放的磨削工艺参数优化方法，旨在平衡磨削工艺中的排放、时间和成本。首先，我们量化了磨削参数与优化目标之间的关系，随后建立了相应的多目标优化模型。然后提出一种改进的多目标蜣螂优化算法（INSDBO）来求解该模型。作为案例研究，我们对柱塞的加工进行了实验。仿真结果表明，优化后，碳排放量、磨削成本和时间分别降低了 11.7%、7.7% 和 6.7%，验证了所提优化方法的有效性。与自适应加权进化算法（AdaW）、传统蜣螂算法（NSDBO）和多阶段多目标进化算法（MSEA）相比，改进的蜣螂优化算法（INSDBO）表现出更优越的性能。这种改进算法可以提出磨削过程中的最佳参数，从而减少碳排放、加工时间和成本。

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引用次数: 0

Robust cooperative hub location optimization considering demand uncertainty and hub disruptions 考虑需求不确定性和枢纽中断的稳健合作枢纽位置优化

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

Computers & Industrial Engineering

Pub Date : 2024-09-26 DOI: 10.1016/j.cie.2024.110591

Amidst the rise of economic globalization and increased commodity trading, the logistics industry is experiencing rapid growth, encountering intricate transportation demands and fierce market competition. Simultaneously, it faces challenges related to infrastructure development and resource allocation efficiency. To enhance the adaptability and robustness of transportation networks when facing uncertain demands and potential hub disruptions, this paper proposes a two-stage robust optimization model for cooperative hub location problem. The model utilizes a hybrid algorithm that effectively combines the global search capability of genetic algorithms with the step-by-step optimization efficiency of Benders decomposition. Case study analyses demonstrate that, irrespective of the uncertainty environment, the cooperative model maintains lower total costs. Particularly in the case of large demand fluctuations, its cost advantages over non-cooperative models become notably prominent, showcasing remarkable performance in meeting service demands and enhancing resource utilization. Additionally, in cooperative networks, hub disruptions have a more significant impact on hub location decisions, with penalty and supplementary costs further exacerbating this influence. These research findings offer crucial insights for management practices: in uncertain market environments, adopting cooperative and robust planning strategies is pivotal for mitigating operational risks. When making decisions on cooperative hub location selection, carriers should comprehensively consider the interaction between uncertainty and economic benefits to achieve an optimal balance between risk and cost, ensuring the sustained economic feasibility of cooperative ventures.

在经济全球化和大宗商品贸易量增加的背景下，物流业正经历着快速发展，面临着错综复杂的运输需求和激烈的市场竞争。与此同时，物流业也面临着基础设施建设和资源配置效率方面的挑战。为了提高运输网络在面对不确定需求和潜在枢纽中断时的适应性和鲁棒性，本文提出了一种针对合作枢纽定位问题的两阶段鲁棒优化模型。该模型采用混合算法，有效结合了遗传算法的全局搜索能力和本德斯分解法的逐步优化效率。案例研究分析表明，无论在何种不确定环境下，合作模型都能保持较低的总成本。特别是在需求波动较大的情况下，与非合作模式相比，合作模式的成本优势更加明显，在满足服务需求和提高资源利用率方面表现突出。此外，在合作网络中，枢纽中断对枢纽位置决策的影响更大，而惩罚成本和补充成本则进一步加剧了这种影响。这些研究结果为管理实践提供了重要启示：在不确定的市场环境中，采用合作和稳健的规划策略对于降低运营风险至关重要。在进行合作枢纽选址决策时，承运商应全面考虑不确定性与经济效益之间的相互作用，以实现风险与成本之间的最佳平衡，确保合作企业的持续经济可行性。

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引用次数: 0

Reliability modeling and analysis of uncertain competing failure systems 不确定竞争故障系统的可靠性建模和分析

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

Computers & Industrial Engineering

Pub Date : 2024-09-26 DOI: 10.1016/j.cie.2024.110583

The competing failure system is quite common in real life, such as automotive system and aerospace system. Two distinct failure modes usually coexist in this type of system: gradual internal degradation and sudden external shock, where the occurrence of any failure mode can lead to the system failure. The system failure such as aircraft accident may cause a terrible loss of human life and property. Hence, it is worth reducing the rate of system failure by improving the system reliability. While, reliability model is the foundation of any research of reliability and epistemic uncertainty exists in the process of modeling and estimating. Therefore, we introduce uncertainty theory to investigate the competing failure system with epistemic uncertainty. The internal degradation and external shock of the system are characterized by an uncertain differential equation and an uncertain renewal process, respectively. The system reliability is defined as the uncertain measure that neither internal degradation nor external shock surpass corresponding thresholds. In addition, some reliability formulas are derived for the systems subjected to extreme shock, cumulative shock, running shock and

δ

-shock, respectively. Finally, a case study with respect to micro-electro-mechanical system is given to show how the proposed model is implemented.

竞争失效系统在现实生活中十分常见，如汽车系统和航空航天系统。这类系统通常同时存在两种不同的失效模式：渐进的内部退化和突然的外部冲击，任何一种失效模式的发生都可能导致系统失效。系统故障（如飞机事故）可能会造成严重的人员伤亡和财产损失。因此，通过提高系统可靠性来降低系统故障率是非常有价值的。可靠性模型是可靠性研究的基础，而在建模和估算过程中存在认识上的不确定性。因此，我们引入不确定性理论来研究具有认识不确定性的竞争失效系统。系统的内部退化和外部冲击分别由不确定微分方程和不确定更新过程表征。系统可靠性被定义为内部退化和外部冲击均不超过相应阈值的不确定度量。此外，还分别推导出了受到极端冲击、累积冲击、运行冲击和 δ 冲击的系统的一些可靠性公式。最后，给出了一个微型机电系统的案例研究，以说明如何实施所提出的模型。

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引用次数: 0

Dynamic soft-kill weapon-target assignment in naval environments 海军环境中的动态软杀伤武器目标分配

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

Computers & Industrial Engineering

Pub Date : 2024-09-26 DOI: 10.1016/j.cie.2024.110606

One of the most significant threats faced by ships is anti-ship missiles. Nowadays, these missiles, equipped with diverse guidance systems, can locate their trajectory and attack the ship. Consequently, ships need to utilize their weapons to attempt to neutralize these threats. This article aims to develop dynamic assignment algorithms to assign a ship’s defensive soft-kill weapons to a set of incoming missiles, to minimize the average damage inflicted on the ship. To this end, initially, a binary linear programming model is developed to solve the static weapon-target assignment problem. Subsequently, a simulation–optimization algorithm and a reinforcement learning-based approach, grounded in the value iteration algorithm, are developed to solve the dynamic weapon-target assignment problem. To compare and evaluate the performance of the developed solution methods, we employ a set of randomly generated test instances. Computational results indicate that the reinforcement learning approach, due to its inherent foresight, outperforms the simulation–optimization approach in reducing the inflicted damages. However, in terms of CPU run time, the simulation–optimization approach is more efficient.

反舰导弹是舰船面临的最大威胁之一。如今，这些导弹配备了不同的制导系统，可以确定其轨迹并攻击舰船。因此，舰船需要利用其武器试图消除这些威胁。本文旨在开发动态分配算法，将舰艇的防御性软杀伤武器分配给一组来袭导弹，以尽量减少对舰艇造成的平均伤害。为此，首先开发了一个二元线性规划模型来解决静态武器目标分配问题。随后，在值迭代算法的基础上，开发了一种模拟优化算法和基于强化学习的方法，以解决动态武器目标分配问题。为了比较和评估所开发的解决方法的性能，我们采用了一组随机生成的测试实例。计算结果表明，强化学习方法因其固有的预见性，在减少造成的损失方面优于模拟优化方法。不过，就 CPU 运行时间而言，模拟优化方法更为高效。

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引用次数: 0

Monitoring and control of air filtration systems: Digital twin based on 1D computational fluid dynamics simulation and experimental data 监测和控制空气过滤系统：基于一维计算流体动力学模拟和实验数据的数字孪生系统

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

Computers & Industrial Engineering

Pub Date : 2024-09-25 DOI: 10.1016/j.cie.2024.110607

This study presents the development of a digital model based on one-dimensional computational fluid dynamics for the monitoring and control of filtering systems used for removing flour, dust, and other particulates from the airflow arriving from various sections of industrial production plants.

Focusing on a pilot plant equipped with a cyclone bag filter, historical experimental data was integrated with the results of a one-dimensional fluid dynamics simulation model to create a digital twin capable of real-time control and regulation of industrial plants. In particular, measured pressure drop data under different clogging conditions were interpolated to generate the characteristic curves of the filter under various clogging conditions, to be implemented within the digital model of the plant. The generated model, validated through a dedicated experimental campaign, accurately predicted the airflow rate and pressure distribution across the plant. The system’s capability to adapt to changing operational conditions, such as clogging, was demonstrated through simulation, highlighting the model’s utility in maintaining the desired operation levels while minimizing the need for extensive sensor networks.

The analyzed case study in the field of air filtration systems aims to fill the gap in the scientific literature related to the application of Digital Twin technology to the control of industrial manufacturing plants. The findings highlight the potential of digital twins in monitoring and control, as well as predictive maintenance, of industrial systems. The findings highlight the potential of Digital Twins in monitoring and control, as well as predictive maintenance, of industrial systems. Future research activities will explore the model’s applicability in failure and anomaly detection, to further enhance predictive maintenance of air filtering systems.

本研究介绍了基于一维计算流体动力学的数字模型的开发情况，该模型用于监测和控制过滤系统，以去除工业生产设备各部分气流中的面粉、灰尘和其他微粒。以配备旋风袋式过滤器的试验设备为重点，将历史实验数据与一维流体动力学仿真模型的结果相结合，创建了一个能够实时控制和调节工业设备的数字孪生系统。特别是，通过对不同堵塞条件下的压降测量数据进行插值，生成了过滤器在各种堵塞条件下的特性曲线，并将其应用于工厂的数字模型中。生成的模型通过专门的实验活动进行验证，准确预测了整个设备的气流速率和压力分布。该系统适应堵塞等不断变化的运行条件的能力通过模拟得到了证明，突出了该模型在保持理想运行水平方面的实用性，同时最大限度地减少了对广泛传感器网络的需求。研究结果凸显了数字孪生技术在工业系统监控和预测性维护方面的潜力。研究结果凸显了数字孪生在工业系统监控和预测性维护方面的潜力。未来的研究活动将探索该模型在故障和异常检测方面的适用性，以进一步加强空气过滤系统的预测性维护。

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引用次数: 0

Global supply chain flow planning for Chinese manufacturing under the BRI: An SFG-DRO method 金砖倡议下中国制造业的全球供应链流程规划：一种 SFG-DRO 方法

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

Computers & Industrial Engineering

Pub Date : 2024-09-25 DOI: 10.1016/j.cie.2024.110605

The Belt and Road Initiative (BRI) has fostered the free flow of commodities and optimal distribution of resources for the global manufacturing supply chain (GMSC), meanwhile confronted with risks and uncertainties. This paper proposes the SFG-DRO method, which can well solve the flow distribution problem of GMSC under the BRI with uncertainties. The proposed method combines trend prediction from the stochastic frontier gravity (SFG) model with 1-Wasserstein fuzzy set-based distributionally robust optimization (DRO). Additionally, this paper integrates the principles of the column and constraint generation (C&CG) algorithm with the particle swarm optimization (PSO) algorithm to handle the above two-stage nonlinear problems efficiently. The results show that the SFG-DRO distribution method significantly reduces transportation costs by 25% and enhances security. By examining flow distribution across three key BRI channels, this paper identifies underexploited markets along the southward channel and substantial market potential with security risks along the northeast sea-land channel, proposing relevant improvement suggestions.

一带一路 "倡议（BRI）促进了全球制造业供应链（GMSC）的商品自由流通和资源优化配置，同时也面临着风险和不确定性。本文提出的 SFG-DRO 方法可以很好地解决 "一带一路 "下全球制造业供应链的流量分配问题。该方法将随机前沿引力（SFG）模型的趋势预测与基于 1-Wasserstein 模糊集的分布鲁棒优化（DRO）相结合。此外，本文还将列和约束生成（C&CG）算法原理与粒子群优化（PSO）算法相结合，有效地处理了上述两阶段非线性问题。研究结果表明，SFG-DRO 分配方法大大降低了 25% 的运输成本，并提高了安全性。通过研究金砖四国三条主要通道的流量分布，本文发现了南向通道沿线未被充分开发的市场，以及东北海陆通道沿线存在安全风险的巨大市场潜力，并提出了相关改进建议。

引用次数: 0

Assessing agrivoltaics potential in Türkiye – A geographical information system (GIS)-based fuzzy multi-criteria decision making (MCDM) approach 评估土耳其的农业光伏潜力--基于地理信息系统（GIS）的模糊多标准决策（MCDM）方法

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

Computers & Industrial Engineering

Pub Date : 2024-09-24 DOI: 10.1016/j.cie.2024.110598

To fulfill the energy requirements through solar photovoltaic (PV) systems, significant land use is needed for solar arrays, access roads, substations, and service buildings. When available land is limited, its use for PV systems creates a major conflict, particularly for crop production. Agrivoltaic (APV) systems are engineered to allocate the same land effectively for both PV energy generation and agricultural activities. Thus, they enable the simultaneous production of food and energy. This study investigates the APV potential of Türkiye using fuzzy multi-criteria decision-making (MCDM) approach and Geographic Information System (GIS) data. The top five cities with the largest cultivated area are identified for assessment of potential APV investments using the fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to the ideal solution (TOPSIS) methods. The FAHP method captures the uncertainty and vagueness in experts’ judgments for criteria prioritization. Next, suitability maps are created using the criteria weights and GIS data to identify potential sites for the APV construction. Finally, the best location is selected Siverek East– Şanlıurfa from fifteen candidate locations from five cities by the TOPSIS method. Sensitivity analysis is conducted to examine the impact of criteria weights on APV suitability maps. The findings of the study provide valuable insights for practitioners in selecting investment locations to harness solar energy sustainably and concurrently facilitate crop production.

要通过太阳能光伏（PV）系统满足能源需求，就需要使用大量土地来建造太阳能电池阵、通路、变电站和服务建筑。在可用土地有限的情况下，将其用于光伏系统会造成很大的冲突，尤其是对农作物生产而言。农业光伏（APV）系统的设计可以有效地将同一块土地用于光伏发电和农业活动。因此，它们能够同时生产粮食和能源。本研究采用模糊多标准决策（MCDM）方法和地理信息系统（GIS）数据，对土耳其的农业光伏潜力进行了调查。采用模糊层次分析法（FAHP）和理想解决方案相似性排序偏好技术（TOPSIS）方法，确定了耕地面积最大的前五个城市，以评估潜在的 APV 投资。FAHP 方法可捕捉专家判断中的不确定性和模糊性，从而确定标准的优先次序。接下来，利用标准权重和 GIS 数据绘制适宜性地图，以确定建造 APV 的潜在地点。最后，通过 TOPSIS 方法，从五个城市的十五个候选地点中选出了最佳地点 Siverek East- Şanlıurfa 。进行了敏感性分析，以研究标准权重对 APV 适宜性地图的影响。研究结果为从业人员选择投资地点提供了有价值的见解，以便可持续地利用太阳能，同时促进作物生产。

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引用次数: 0