Application of Mathematical Methods in Industrial Engineering and Management

A special issue of Mathematics (ISSN 2227-7390).

Deadline for manuscript submissions: closed (10 May 2023) | Viewed by 26113

Special Issue Editors

Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu 300, Taiwan
Interests: network reliability; systems quality management; process reengineering; service science & management
Department of Electrical & Computer Engineering, University of Massachusetts Dartmouth, North Dartmouth, MA, USA
Interests: system reliability; software reliability engineering; simulation
Department of Business Administration, Feng Chia University, Taichung 407, Taiwan
Interests: network analysis; system reliability; process capability analysis
Special Issues, Collections and Topics in MDPI journals
Department of Industrial Engineering and Management, National Quemoy University, Kinmen County 892, Taiwan
Interests: network reliability; six sigma management; process control

Special Issue Information

Dear Colleagues,

In this Special Issue, we focus on applications of mathematical methods in industrial engineering and management, and invite related high quality papers covering theory and practice. Developing and applying mathematical methods, such as operations research, stochastic processes, and statistics, in order to measure the performance and solve engineering problems associated with real systems are truly crucial tasks. Several practical systems can be involved in related problems, including computer, logistic, and production systems. The management implications, improvement, and decisions made based on system performance evaluation are all within the scope.

Hence, we invite related high quality papers to solve practical problems from industrial engineering and management through mathematical approaches. Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. Potential topics include, but are not limited to:

  • Operations research applications
  • Quality Measurement
  • Performance Evaluation
  • Applications in Production, Manufacturing and Logistics
  • Statistics in Production, Manufacturing and Logistics
  • Reliability Engineering
  • Decision support
  • Application in Computing, Artificial Intelligence
  • Information Management
  • Management Science
  • Soft Computing on Production, Manufacturing and Logistics

Prof. Dr. Yi-Kuei Lin
Dr. Lance Fiondella
Dr. Cheng-Fu Huang
Dr. Ping-Chen Chang
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Operation research applications
  • Statistics applications
  • Optimization
  • Mathematical modeling
  • Reliability
  • Decision analysis
  • Artificial intelligence applications

Published Papers (12 papers)

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Research

26 pages, 639 KiB  
Article
A Hybrid Stochastic Deterministic Algorithm for Solving Unconstrained Optimization Problems
by Ahmad M. Alshamrani, Adel Fahad Alrasheedi, Khalid Abdulaziz Alnowibet, Salem Mahdi and Ali Wagdy Mohamed
Mathematics 2022, 10(17), 3032; https://0-doi-org.brum.beds.ac.uk/10.3390/math10173032 - 23 Aug 2022
Cited by 9 | Viewed by 1282
Abstract
In this paper, a new deterministic method is proposed. This method depends on presenting (suggesting) some modifications to existing parameters of some conjugate gradient methods. The parameters of our suggested method contain a mix of deterministic and stochastic parameters. The proposed method is [...] Read more.
In this paper, a new deterministic method is proposed. This method depends on presenting (suggesting) some modifications to existing parameters of some conjugate gradient methods. The parameters of our suggested method contain a mix of deterministic and stochastic parameters. The proposed method is added to a line search algorithm to make it a globally convergent method. The convergence analysis of the method is established. The gradient vector is estimated by a finite difference approximation approach, and a new step-size h of this approach is generated randomly. In addition, a set of stochastic parameter formulas is constructed from which some solutions are generated randomly for an unconstrained problem. This stochastic technique is hybridized with the new deterministic method to obtain a new hybrid algorithm that finds an approximate solution for the global minimization problem. The performance of the suggested hybrid algorithm is tested in two sets of benchmark optimization test problems containing convex and non-convex functions. Comprehensive comparisons versus four other hybrid algorithms are listed in this study. The performance profiles are utilized to evaluate and compare the performance of the five hybrid algorithms. The numerical results show that our proposed hybrid algorithm is promising and competitive for finding the global optimum point. The comparison results between the performance of our suggested hybrid algorithm and the other four hybrid algorithms indicate that the proposed algorithm is competitive with, and in all cases superior to, the four algorithms in terms of the efficiency, reliability, and effectiveness for finding the global minimizers of non-convex functions. Full article
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27 pages, 5333 KiB  
Article
A Non-Invasive Method to Evaluate Fuzzy Process Capability Indices via Coupled Applications of Artificial Neural Networks and the Placket–Burman DOE
by Iván E. Villalón-Turrubiates, Rogelio López-Herrera, Jorge L. García-Alcaraz, José R. Díaz-Reza, Arturo Soto-Cabral, Iván González-Lazalde, Gerardo Grijalva-Avila and José L. Rodríguez-Álvarez
Mathematics 2022, 10(16), 3000; https://0-doi-org.brum.beds.ac.uk/10.3390/math10163000 - 19 Aug 2022
Cited by 1 | Viewed by 1102
Abstract
The capability analysis of a process against requirements is often an instrument of change. The traditional and fuzzy process capability approaches are the most useful statistical techniques for determining the intrinsic spread of a controlled process for establishing realistic specifications and use for [...] Read more.
The capability analysis of a process against requirements is often an instrument of change. The traditional and fuzzy process capability approaches are the most useful statistical techniques for determining the intrinsic spread of a controlled process for establishing realistic specifications and use for comparative processes. In the industry, the traditional approach is the most commonly used instrument to assess the impact of continuous improvement projects. However, these methods used to evaluate process capability indices could give misleading results because the dataset employed corresponds to the final product/service measures. This paper reviews an alternative procedure to assess the fuzzy process capability indices based on the statistical methodology involved in the modeling and design of experiments. Firstly, a model with reasonable accuracy is developed using a neural network approach. This model is embedded in a graphic user interface (GUI). Using the GUI, an experimental design is carried out, first to know the membership function of the process variability and then include this variability in the model. Again, an experimental design identifies the improved operating conditions for the significative independent variables. A new dataset is generated with these operating conditions, including the minimum error reached for each independent variable. Finally, the GUI is used to get a new prediction for the response variable. The fuzzy process capability indices are determined using the triangular membership function and the predicted response values. The feasibility of the proposed method was validated using a random data set corresponding to the basis weight of a papermaking process. The results indicate that the proposed method provides a better overview of the process performance, showing its true potential. The proposed method can be considered non-invasive. Full article
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25 pages, 474 KiB  
Article
The Stochastic Team Orienteering Problem with Position-Dependent Rewards
by Javier Panadero, Eva Barrena, Angel A. Juan and David Canca
Mathematics 2022, 10(16), 2856; https://0-doi-org.brum.beds.ac.uk/10.3390/math10162856 - 10 Aug 2022
Viewed by 1322
Abstract
In this paper, we analyze both the deterministic and stochastic versions of a team orienteering problem (TOP) in which rewards from customers are dynamic. The typical goal of the TOP is to select a set of customers to visit in order to maximize [...] Read more.
In this paper, we analyze both the deterministic and stochastic versions of a team orienteering problem (TOP) in which rewards from customers are dynamic. The typical goal of the TOP is to select a set of customers to visit in order to maximize the total reward gathered by a fixed fleet of vehicles. To better reflect some real-life scenarios, we consider a version in which rewards associated with each customer might depend upon the order in which the customer is visited within a route, bonusing the first clients and penalizing the last ones. In addition, travel times are modeled as random variables. Two mixed-integer programming models are proposed for the deterministic version, which is then solved using a well-known commercial solver. Furthermore, a biased-randomized iterated local search algorithm is employed to solve this deterministic version. Overall, the proposed metaheuristic algorithm shows an outstanding performance when compared with the optimal or near-optimal solutions provided by the commercial solver, both in terms of solution quality as well as in computational times. Then, the metaheuristic algorithm is extended into a full simheuristic in order to solve the stochastic version of the problem. A series of numerical experiments allows us to show that the solutions provided by the simheuristic outperform the near-optimal solutions obtained for the deterministic version of the problem when the latter are used in a scenario under conditions of uncertainty. In addition, the solutions provided by our simheuristic algorithm for the stochastic version of the problem offer a higher reliability level than the ones obtained with the commercial solver. Full article
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15 pages, 631 KiB  
Article
Examining Consumer’s Intention to Adopt AI-Chatbots in Tourism Using Partial Least Squares Structural Equation Modeling Method
by Farrukh Rafiq, Nikhil Dogra, Mohd Adil and Jei-Zheng Wu
Mathematics 2022, 10(13), 2190; https://0-doi-org.brum.beds.ac.uk/10.3390/math10132190 - 23 Jun 2022
Cited by 19 | Viewed by 3819
Abstract
Artificial intelligence (AI) is an important link between online consumers and the tourism industry. AI-chatbots are the latest technological advancement that have shaped the tourism industry. AI-chatbots are a relatively new technology in the hospitality and tourism industries, but little is known about [...] Read more.
Artificial intelligence (AI) is an important link between online consumers and the tourism industry. AI-chatbots are the latest technological advancement that have shaped the tourism industry. AI-chatbots are a relatively new technology in the hospitality and tourism industries, but little is known about their use. The study aims to identify factors influencing AI-chatbot adoption and their use in improving customer engagement and experiences. Using an offline survey, researchers collected data from 530 respondents. Using the structural equation modeling technique, the conceptual model was empirically tested. According to the results, the S-O-R theoretical framework is suitable for evaluating chatbot adoption intentions. Additionally, the structural model supported the ten hypotheses, validating the suggested directions of substantial impacts. In addition to practitioners and tourism managers, this study also has broad implications for scholars. Full article
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23 pages, 1172 KiB  
Article
Performance of Channel Members under Emission-Sensitive Demand for Green Supply Chain Management: A Game Theory Approach
by Rofin T.M., Umakanta Mishra and Jei-Zheng Wu
Mathematics 2022, 10(11), 1879; https://0-doi-org.brum.beds.ac.uk/10.3390/math10111879 - 30 May 2022
Cited by 1 | Viewed by 1476
Abstract
The skyrocketing growth of e-commerce and traditional retailing contributes to a large proportion of carbon emissions in any supply chain. Nevertheless, the literature related to carbon emission has focused on manufacturers and their potential for emission reduction. Therefore, it is imperative to understand [...] Read more.
The skyrocketing growth of e-commerce and traditional retailing contributes to a large proportion of carbon emissions in any supply chain. Nevertheless, the literature related to carbon emission has focused on manufacturers and their potential for emission reduction. Therefore, it is imperative to understand the role of the retailing sector in reducing carbon emissions. Therefore, this study considers emission-sensitive demands which are faced by an r-store (brick and mortar retailer) and an e-store (online retailer) under different channel power structures. The competition between the channel members is modeled using game theory for the following channel structures, i.e., (i) r-store and e-store have commensurate channel power, (ii) r-store holds higher channel power, and (iii) e-store holds higher channel power. Equilibrium analysis was carried out to obtain the optimal pricing strategies and the r-store’s optimal profit and e-store. Further, the pricing strategies and resulting sales volumes were compared analytically and followed by a numerical validation. Three subcases were considered under numerical examples based on the parameter values with special reference to the base demand. It was found that competition between the r-store and the e-store having commensurate channel power will make them worse off. Therefore, the channel leadership is neither helping the r-store nor the e-store obtain more profit when the customer demand is emission sensitive. Full article
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35 pages, 5862 KiB  
Article
Enhancing Supply Chain Agility with Industry 4.0 Enablers to Mitigate Ripple Effects Based on Integrated QFD-MCDM: An Empirical Study of New Energy Materials Manufacturers
by Chih-Hung Hsu, Xu He, Ting-Yi Zhang, An-Yuan Chang, Wan-Ling Liu and Zhi-Qiang Lin
Mathematics 2022, 10(10), 1635; https://0-doi-org.brum.beds.ac.uk/10.3390/math10101635 - 11 May 2022
Cited by 9 | Viewed by 2586
Abstract
Given the increasing complexity of the global supply chain, it is an important issue to enhance the agilities of enterprises that manufacture new energy materials to reduce the ripple effects of supply chains. Quality function deployment (QFD) has been applied in many areas [...] Read more.
Given the increasing complexity of the global supply chain, it is an important issue to enhance the agilities of enterprises that manufacture new energy materials to reduce the ripple effects of supply chains. Quality function deployment (QFD) has been applied in many areas to solve multi-criteria decision making (MCDM) problems successfully. However, there is still lack of sufficient research on the use of MCDM to develop two house-of-quality systems in the supply chain of new energy materials manufacturing enterprises to determine ripple effect factors (REFs), supply chain agility indicators (SCAIs), and industry 4.0 enablers (I4Es). This study aimed to develop a valuable decision framework by integrating MCDM and QFD; using key I4Es to enhance the agility of supply chain and reduce or mitigate its ripple effects ultimately, this study provides an effective method for new energy materials manufacturers to develop supply chains that can rapidly respond to change and uncertainty. The case study considered China’s largest new energy materials manufacturing enterprise as the object and obtained important management insights, as well as practical significance, from implementing the proposed research framework. The study found the following to be the most urgent I4Es required to strengthen the agility of supply chain and reduce the key REFs: ensuring data privacy and security, guarding against legal risks, adopting digital transformation investment to improve economic efficiency, ramming IT infrastructure for big data management, and investing and using the new equipment of Industry 4.0. When these measures are improved, the agility of the supply chain can be improved, such as long-term cooperation with partners to strengthen trust relationships, supply chain information transparency and visualization to quickly respond to customer needs, and improving customer service levels and satisfaction. Finally, REFs, such as the bullwhip effect caused by inaccurate prediction, facility failure, and poor strain capacity caused by supply chain disruption, can be alleviated or eliminated. The proposed framework provides an effective strategy for formulating I4Es to strengthen supply chain agility (SCA) and mitigate ripple effects, as well as provides a reference for supply chain management of other manufacturing enterprises in the field of cleaner production. Full article
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34 pages, 1297 KiB  
Article
Agent Scheduling in Unrelated Parallel Machines with Sequence- and Agent–Machine–Dependent Setup Time Problem
by Jesús Isaac Vázquez-Serrano, Leopoldo Eduardo Cárdenas-Barrón and Rodrigo E. Peimbert-García
Mathematics 2021, 9(22), 2955; https://0-doi-org.brum.beds.ac.uk/10.3390/math9222955 - 19 Nov 2021
Cited by 2 | Viewed by 1598
Abstract
Assignation-sequencing models have played a critical role in the competitiveness of manufacturing companies since the mid-1950s. The historic and constant evolution of these models, from simple assignations to complex constrained formulations, shows the need for, and increased interest in, more robust models. Thus, [...] Read more.
Assignation-sequencing models have played a critical role in the competitiveness of manufacturing companies since the mid-1950s. The historic and constant evolution of these models, from simple assignations to complex constrained formulations, shows the need for, and increased interest in, more robust models. Thus, this paper presents a model to schedule agents in unrelated parallel machines that includes sequence and agent–machine-dependent setup times (ASUPM), considers an agent-to-machine relationship, and seeks to minimize the maximum makespan criteria. By depicting a more realistic scenario and to address this NP-hard problem, six mixed-integer linear formulations are proposed, and due to its ease of diversification and construct solutions, two multi-start heuristics, composed of seven algorithms, are divided into two categories: Construction of initial solution (designed algorithm) and improvement by intra (tabu search) and inter perturbation (insertions and interchanges). Three different solvers are used and compared, and heuristics algorithms are tested using randomly generated instances. It was found that models that linearizing the objective function by both job completion time and machine time is faster and related to the heuristics, and presents an outstanding level of performance in a small number of instances, since it can find the optimal value for almost every instance, has very good behavior in a medium level of instances, and decent performance in a large number of instances, where the relative deviations tend to increase concerning the small and medium instances. Additionally, two real-world applications of the problem are presented: scheduling in the automotive industry and healthcare. Full article
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18 pages, 371 KiB  
Article
EM Algorithm for Mixture Distributions Model with Type-I Hybrid Censoring Scheme
by Tzong-Ru Tsai, Yuhlong Lio and Wei-Chen Ting
Mathematics 2021, 9(19), 2483; https://0-doi-org.brum.beds.ac.uk/10.3390/math9192483 - 04 Oct 2021
Cited by 4 | Viewed by 1401
Abstract
An expectation–maximization (EM) likelihood estimation procedure is proposed to obtain the maximum likelihood estimates of the parameters in a mixture distributions model based on type-I hybrid censored samples when the mixture proportions are unknown. Three bootstrap methods are applied to construct the confidence [...] Read more.
An expectation–maximization (EM) likelihood estimation procedure is proposed to obtain the maximum likelihood estimates of the parameters in a mixture distributions model based on type-I hybrid censored samples when the mixture proportions are unknown. Three bootstrap methods are applied to construct the confidence intervals of the model parameters. Monte Carlo simulations are conducted to evaluate the performance of the proposed methods. Simulation results show that the proposed methods can perform well to obtain reliable point and interval estimation results. Three examples are used to illustrate the applications of the proposed methods. Full article
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23 pages, 2195 KiB  
Article
A Stochastic Approach for Product Costing in Manufacturing Processes
by Paulo Afonso, Vishad Vyas, Ana Antunes, Sérgio Silva and Boris P. J. Bret
Mathematics 2021, 9(18), 2238; https://0-doi-org.brum.beds.ac.uk/10.3390/math9182238 - 12 Sep 2021
Cited by 4 | Viewed by 2430
Abstract
Nowadays, manufacturing companies are characterized by complex systems with multiple products being manufactured in multiple assembly lines. In such situations, traditional costing systems based on deterministic cost models cannot be used. This paper focuses on developing a stochastic approach to costing systems that [...] Read more.
Nowadays, manufacturing companies are characterized by complex systems with multiple products being manufactured in multiple assembly lines. In such situations, traditional costing systems based on deterministic cost models cannot be used. This paper focuses on developing a stochastic approach to costing systems that considers the variability in the process cycle time of the different workstations in the assembly line. This approach provides a range of values for the product costs, allowing for a better perception of the risk associated to these costs instead of providing a single value of the cost. The confidence interval for the mean and the use of quartiles one and three as lower and upper estimates are proposed to include variability and risk in costing systems. The analysis of outliers and some statistical tests are included in the proposed approach, which was applied in a tier 1 company in the automotive industry. The probability distribution of the possible range of values for the bottleneck’s cycle time showcase all the possible values of product cost considering the process variability and uncertainty. A stochastic cost model allows a better analysis of the margins and optimization opportunities as well as investment appraisal and quotation activities. Full article
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20 pages, 3174 KiB  
Article
An Inventory Model for Imperfect Quality Products with Rework, Distinct Holding Costs, and Nonlinear Demand Dependent on Price
by Leopoldo Eduardo Cárdenas-Barrón, María José Lea Plaza-Makowsky, María Alejandra Sevilla-Roca, José María Núñez-Baumert and Buddhadev Mandal
Mathematics 2021, 9(12), 1362; https://0-doi-org.brum.beds.ac.uk/10.3390/math9121362 - 12 Jun 2021
Cited by 14 | Viewed by 1676
Abstract
Traditionally, the inventory models available in the literature assume that all articles in the purchased lot are perfect and the demand is constant. However, there are many causes that provoke the presence of defective goods and the demand is dependent on some factors. [...] Read more.
Traditionally, the inventory models available in the literature assume that all articles in the purchased lot are perfect and the demand is constant. However, there are many causes that provoke the presence of defective goods and the demand is dependent on some factors. In this direction, this paper develops an economic order quantity (EOQ) inventory model for imperfect and perfect quality items, taking into account that the imperfect ones are sent as a single lot to a repair shop for reworking. After reparation, the items return to the inventory system and are inspected again. Depending on the moment at which the reworked lot arrives to the inventory system, two scenarios can occur: Case 1: The reworked lot enters when there still exists inventory; and Case 2: The reworked lot comes into when the inventory level is zero. Furthermore, it is considered that the holding costs of perfect and imperfect items are distinct. The demand of the products is nonlinear and dependent on price, which follows a polynomial function. The main goal is to optimize jointly the lot size and the selling price such that the expected total profit per unit of time is maximized. Some theoretic results are derived and algorithms are developed for determining the optimal solution for each modeled case. It is worth mentioning that the proposed inventory model is a general model due to the fact that this contains some published inventory models as particular cases. With the aim to illustrate the use of the proposed inventory model, some numerical examples are solved. Full article
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13 pages, 737 KiB  
Article
Assess the Impacts of Discount Policies on the Reliability of a Stochastic Air Transport Network
by Thi-Phuong Nguyen
Mathematics 2021, 9(9), 965; https://0-doi-org.brum.beds.ac.uk/10.3390/math9090965 - 25 Apr 2021
Viewed by 1331
Abstract
In this study, an algorithm for reliability evaluation is proposed in order to assess the discount policy based on its effect on an air transport network. An air transport network is a typical stochastic air transport network (SATN) because its capacity (available seats) [...] Read more.
In this study, an algorithm for reliability evaluation is proposed in order to assess the discount policy based on its effect on an air transport network. An air transport network is a typical stochastic air transport network (SATN) because its capacity (available seats) is regarded as stochastic. Under different discount policies, the term “reliability” refers to the ability to meet a certain travel demand within a limited budget. To better describe the flow of SATN, the methods of the sum of disjoint products and minimal paths are combined in the proposed algorithm. A reliability analysis is conducted at ranges of budgets and travel demands for a more accurate assessment. The outcomes of this study help the travel agents assess and select an appropriate discount policy, which is one of the important contributions. This study also contributes to enhancing the reliability fluctuation under the impact of multiple discount policies. Full article
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15 pages, 2108 KiB  
Article
Data Envelopment Analysis Approach to Energy-Saving Projects Selection in an Energy Service Company
by Gabriel Villa, Sebastián Lozano and Sandra Redondo
Mathematics 2021, 9(2), 200; https://0-doi-org.brum.beds.ac.uk/10.3390/math9020200 - 19 Jan 2021
Cited by 10 | Viewed by 2124
Abstract
Project selection is a common problem for many companies. Specifically, it consists in identifying which projects should be selected with regard to their economic efficiency, i.e., the projects that maximise the profit they bring in while minimising the cost of the resources consumed. [...] Read more.
Project selection is a common problem for many companies. Specifically, it consists in identifying which projects should be selected with regard to their economic efficiency, i.e., the projects that maximise the profit they bring in while minimising the cost of the resources consumed. In this paper, we have focused our interest on energy service companies because of the importance of a convenient selection of their projects. In these types of companies, the attractiveness of a project depends on both the profit estimations obtained in simulations of the energy systems to be improved, as well as the probability that the project will be awarded (e.g., in local government bids, where typically several energy service companies compete to win the bid). We propose a new project selection method, especially tailored to energy service companies and based on centralised data envelopment analysis models with limited availability of the resources. This contrasts with all existing project selection methods and allows the proposed approach to make more efficient use of the limited resources. We have applied the model to a real-world case by selecting projects in a Spanish energy service company, showing the benefits of applying this approach, and comparing the results obtained with other data envelopment analysis project selection approaches. Full article
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