Computers & Operations Research最新文献

Q-learning-driven multi-population cooperative evolutionary algorithm with local search for scheduling of network-shared manufacturing resources

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-29 DOI: 10.1016/j.cor.2025.107076

Liping Xu , Tao Zhou , Kai Li , Jianfu Chen , Han Zhang

{"title":"Q-learning-driven multi-population cooperative evolutionary algorithm with local search for scheduling of network-shared manufacturing resources","authors":"Liping Xu , Tao Zhou , Kai Li , Jianfu Chen , Han Zhang","doi":"10.1016/j.cor.2025.107076","DOIUrl":"10.1016/j.cor.2025.107076","url":null,"abstract":"<div><div>The variability in the availability of network-shared manufacturing resources and the release times of orders pose challenges to the operational decision-making of industrial internet platforms. This paper addresses these characteristics by studying the identical parallel machine scheduling problem, aiming to minimize total weighted tardiness under constraints of arbitrary release times and multiple machine unavailability periods. To address this research problem, a decoding mechanism based on machine idle periods is first proposed, effectively solving the impact of machine unavailability periods on the scheduling scheme. Secondly, a multi-population cooperative evolutionary algorithm is designed in which the mechanisms of selection, crossover, mutation, and information exchange between populations are improved. The optimal scheduling properties of two jobs on the same machine and different machines are analyzed, resulting in the design of two local search mechanisms. Additionally, Q-learning is introduced to enhance the adaptability of algorithm parameters by dynamically adjusting them within the multi-population cooperative evolutionary algorithm, resulting in a Q-learning-driven multi-population cooperative evolutionary algorithm with local search (Q-MPCEA-LS). Finally, comparative experiments between the Q-MPCEA-LS algorithm and various metaheuristic algorithms are conducted. The experimental results show that, across all instances, the average relative error in the average value metric of the Q-MPCEA-LS algorithm is 40.0%, 0.1%, 44.2%, and 75.9% lower than that of Q-MPCEA-LS without local search, Q-MPCEA-LS without Q-learning-based dynamic parameter adjustment, the iterative hybrid metaheuristic algorithm, and the hybrid genetic immune algorithm, respectively. These results validate the effectiveness of the individual components and the overall effectiveness of the Q-MPCEA-LS algorithm.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107076"},"PeriodicalIF":4.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 hybrid approach using ant colony optimisation for integrated scheduling of production and transportation tasks within flexible manufacturing systems

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-26 DOI: 10.1016/j.cor.2025.107059

Naihui He , M’hammed Sahnoun , David Zhang , Belgacem Bettayeb

{"title":"A hybrid approach using ant colony optimisation for integrated scheduling of production and transportation tasks within flexible manufacturing systems","authors":"Naihui He , M’hammed Sahnoun , David Zhang , Belgacem Bettayeb","doi":"10.1016/j.cor.2025.107059","DOIUrl":"10.1016/j.cor.2025.107059","url":null,"abstract":"<div><div>This paper studies the integrated scheduling problem in flexible manufacturing systems (FMS), where flexible machines and Automated Guided Vehicles (AGV) shared by production jobs are scheduled simultaneously in an integrated manner. Routing flexibility, a crucial advantage of FMS, enabling a job to be handled via alternative machine combinations, is involved. To address this problem, we propose a novel hybrid approach using Ant Colony Optimisation (ACO), which employs a two-element vector structure to model the ACO decision nodes. Each node represents an operation from a job assigned to a particular machine. During the ACO process, to decide a node for next movement, an ant first assesses potential nodes through a node scheduling procedure with two consecutive steps: firstly, using a heuristic vehicle assignment method, an AGV is designated and scheduled for the operation specified in a node. Following this, based on the established transportation timeline, the operation’s production schedule on the assigned machine is determined. Subsequently, the node selection is guided by the pheromone information on potential paths and the heuristic data of potential nodes derived from their scheduling information. To avoid local optima, multiple heuristic rules are incorporated in the ACO, with one chosen randomly for node selection each time. Numerical tests show that our proposed approach outperforms contemporary metaheuristic approaches in the literature. In addition, its efficiency of handling complex problem instances is also assessed and demonstrated.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107059"},"PeriodicalIF":4.1,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel decision support framework for multi-objective aircraft routing problem

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-26 DOI: 10.1016/j.cor.2025.107058

Francisco López-Ramos , Francisco Benita , Nuno Antunes Ribeiro

{"title":"A novel decision support framework for multi-objective aircraft routing problem","authors":"Francisco López-Ramos , Francisco Benita , Nuno Antunes Ribeiro","doi":"10.1016/j.cor.2025.107058","DOIUrl":"10.1016/j.cor.2025.107058","url":null,"abstract":"<div><div>The aircraft routing problem has received extensive attention from researchers, prompting the utilization of diverse problem-solving approaches and the use of various metrics to inform decision-making. Despite the wealth of research, airline managers often rely heavily on their own experience when evaluating potential aircraft routing solutions. To bridge this gap and empower airline managers with a robust decision-making process, this paper proposes a novel modeling framework and decision support tool for solving the Multi-Objective Aircraft Routing Problem. Our methodological framework comprises 3 modules: (i) an efficient data handling and storage process to manage a large volume of data and ensure data tractability; (ii) a novel mixed-integer linear programming model to effectively solve the aircraft routing problem within 1 to 5 min of computation, even at large instances; (iii) a multi-objective algorithmic framework that effectively employs parallelization techniques to generate Pareto-optimal frontiers within 30 min of computation. The three components are integrated into an unified decision support tool that empowers airline managers to visualize and evaluate various aircraft routing solutions, considering multiple objectives simultaneously while leveraging the use of multi-criteria methods. To validate the proposed approach, historic data from AirAsia is used for testing. The results demonstrate the tool’s capability to generate high-quality solutions that strike a balance between conflicting objectives, affirming its practicality and effectiveness in real-world applications.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107058"},"PeriodicalIF":4.1,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Modelling a capacitated location problem for designing multimodal vaccine distribution network using a novel Health Emergency Susceptibility Index

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-26 DOI: 10.1016/j.cor.2025.107056

Biswajit Kar, Mamata Jenamani

{"title":"Modelling a capacitated location problem for designing multimodal vaccine distribution network using a novel Health Emergency Susceptibility Index","authors":"Biswajit Kar, Mamata Jenamani","doi":"10.1016/j.cor.2025.107056","DOIUrl":"10.1016/j.cor.2025.107056","url":null,"abstract":"<div><div>Health emergency due to the outbreak of a contagious virus augments the need for effective vaccine distribution strategies to control its spread. This paper suggests a two-phase strategy to solve this problem. Phase I constructs a Health Emergency Susceptibility Index for each region, considering the disease data and comorbidity situation. Phase II uses the HESI and proposes three versions of priority weights for different application scenarios. These are used as the priority weights to formulate a capacitated location problem with a multimodal network and multiple types of refrigerators. The model considers additional factors like storage capacity, locations, transportation distances (including air and ground options), costs (maintenance and transportation), and vehicle capacity. To solve the model for large networks, the paper suggests a solution approach using Benders Decomposition with extreme directions. To validate the models, we examine the case of COVID-19 vaccine distribution in India. To assess the impact of the Susceptibility Index on facility locations, proposed weightage versions are compared with a version that does not use the index. The results show that one of the three versions with weighting schemes based on the population-to-susceptibility ratio leads to the most cost-effective distribution strategy, ensuring coverage of all susceptible regions. Furthermore, the Decomposition-based solution significantly improves computational efficiency, solving the problem over fifty times faster than the commercial solver.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107056"},"PeriodicalIF":4.1,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 enhanced rescheduling based on hybrid strategy in intermodal container terminal

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-25 DOI: 10.1016/j.cor.2025.107053

Jiaqi Li , Daofang Chang , Furong Wen

{"title":"Digital twin enhanced rescheduling based on hybrid strategy in intermodal container terminal","authors":"Jiaqi Li , Daofang Chang , Furong Wen","doi":"10.1016/j.cor.2025.107053","DOIUrl":"10.1016/j.cor.2025.107053","url":null,"abstract":"<div><div>Enhancing the operational efficiency of the railway center station (RCS) is a critical task for intermodal container terminals. Unlike most existing studies that focus on a single container flow, this study investigates the cooperative scheduling of internal container trucks (ICTs) and railway cranes (RCs) for multiple container flows. A mixed-integer programming model is developed to minimize the maximum completion time, the waiting time of external container trucks (ECTs), and the transportation time of ICTs. To generate an optimized baseline schedule, a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is employed. From a practical operational perspective, however, the baseline schedule must effectively address uncertainties in real-time. Therefore, we propose a proactive-reactive and global-local hybrid rescheduling strategy based on digital twin (DT). The DT facilitates uncertainty monitoring, rescheduling plan generation, simulation, and iterative optimization. The hybrid strategy consists of: (1) a global rescheduling optimization model, which is proactively triggered periodically or reactively triggered due to cumulative errors, aiming to maximize schedule stability; and (2) a local short-interval recovery policy, which is reactively triggered to handle uncertainties occurring between two consecutive global rescheduling points. A case study is conducted to demonstrate the effectiveness of the proposed rescheduling strategy in handling delayed ECT arrivals and other uncertainties. The results highlight the efficiency of the DT-enhanced methodology in improving RC and ICT collaboration. Sensitivity analysis further identifies appropriate threshold settings and equipment configurations. The results show that the application of the DT-enhanced rescheduling methodology in the RCS helps operators to make optimized and timely decisions.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107053"},"PeriodicalIF":4.1,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Minimizing the expected cybersecurity loss in a software supply chain through scheduling scanning jobs

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-25 DOI: 10.1016/j.cor.2025.107064

Jen-Ya Wang

{"title":"Minimizing the expected cybersecurity loss in a software supply chain through scheduling scanning jobs","authors":"Jen-Ya Wang","doi":"10.1016/j.cor.2025.107064","DOIUrl":"10.1016/j.cor.2025.107064","url":null,"abstract":"<div><div>Third-party cybersecurity providers in a software supply chain execute scanning jobs according to business policies and government regulations, tailoring responses to each node’s unique attributes and risks. Traditionally, providers might use various tools at different times without coordination, leading to resource bottlenecks. This study introduces a novel approach to scanning job scheduling, addressing the unique challenge where the marginal benefit of scanning time varies non-linearly, unlike traditional job scheduling problems. The findings reveal that upgrading a scanning strategy by one level can quantify the reduced loss, providing a foundation for efficient resource allocation in large-scale supply chains. A branch-and-bound algorithm is developed to generate the optimal schedules, serving as a benchmark for evaluating other metaheuristic algorithms. Furthermore, this study proposes an innovative genetic algorithm incorporating dynamic crossover or mutation rates, as well as mechanisms to prevent premature convergence and improve performance. This approach demonstrates practical scalability and efficiency in scheduling scanning jobs across 300 nodes, ensuring adaptability to real-world supply chains.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107064"},"PeriodicalIF":4.1,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Optimizing strategic and operational decisions of car sharing systems under demand uncertainty and substitution

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-24 DOI: 10.1016/j.cor.2025.107052

Beste Basciftci , Esra Koca , Sinan Emre Kosunda

{"title":"Optimizing strategic and operational decisions of car sharing systems under demand uncertainty and substitution","authors":"Beste Basciftci , Esra Koca , Sinan Emre Kosunda","doi":"10.1016/j.cor.2025.107052","DOIUrl":"10.1016/j.cor.2025.107052","url":null,"abstract":"<div><div>Car sharing is an efficient way to improve mobility, reduce the use of personal vehicles, and lessen the associated carbon emissions. Due to increasing environmental awareness of customers and government regulations, car sharing providers must be careful about the composition of their vehicle fleet to meet diverse customer demand through vehicle types with different carbon emission levels. In this study, for a car sharing company, we consider the problems of determining service regions and purchasing decisions with a mixed fleet of vehicles under budget and carbon emission constraints, and the deployment of these vehicles to service regions under uncertain one-way and round-trip rental requests over a multi-period planning horizon. We further introduce the concept of “substitution” to the car sharing operations that provides customers with alternative vehicle options when their preferred type is unavailable. To address this complex problem, we propose a novel two-stage stochastic mixed-integer program leveraging spatial–temporal networks and multicommodity flows to capture these strategic and operational decisions of this system over the planning horizon while allowing substitution in operations. We further prove that the corresponding second-stage problem of the proposed program has a totally unimodular constraint matrix. Taking advantage of this result, we develop a branch-and-cut-based decomposition algorithm with various computational enhancements. We present an extensive computational study that highlights the value of the proposed models from different perspectives and demonstrates the performance of the proposed solution algorithm with significant speedups. Our case study provides insights for region opening and fleet allocation plans under demand uncertainty and demonstrates the value of introducing substitution to car sharing operations and the importance of integrating strategic and operational decisions and obtaining stochastic solutions.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107052"},"PeriodicalIF":4.1,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Optimizing blocking and starving delays in sequential zone order picking systems through time-decomposed workload balancing

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-23 DOI: 10.1016/j.cor.2025.107060

Jeongwon Park , Soondo Hong

{"title":"Optimizing blocking and starving delays in sequential zone order picking systems through time-decomposed workload balancing","authors":"Jeongwon Park , Soondo Hong","doi":"10.1016/j.cor.2025.107060","DOIUrl":"10.1016/j.cor.2025.107060","url":null,"abstract":"<div><div>Sequential zone order picking systems frequently encounter blocking delays when a tote cannot proceed to the next zone because it is occupied, and starving delays when a tote remains unassigned to a zone. General approaches to minimize delays include balancing the total workload across zones, grouping the orders into batches, or optimizing the order release sequences. However, the issue of temporal workload imbalances caused by instantaneous differences in processing time between zones has not been addressed. Since temporal workload imbalances result in delays, this study proposes the decomposition of workloads into time slots and develops a temporal workload balancing model (TBM) that incorporates batching and sequencing based on time slot decomposition. We also develop an adaptive large neighborhood search (ALNS) heuristic model to tackle large-scale practical problems of temporal workload imbalance. In simulation experiments, we compare the TBM model to alternative batching strategies in an order picking environment featuring consecutive batch windows. Our findings reveal that the TBM model yields an average reduction in makespan of 27.65% and 15.99% compared to random strategy and baseline method. We conclude that temporal workload balancing can minimize blocking and starving delays and maximize order picking productivity.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107060"},"PeriodicalIF":4.1,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 distributionally robust optimisation with joint chance constraints approach for location-routing problem in urban search and rescue operations

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-18 DOI: 10.1016/j.cor.2025.107051

Kamran Sarmadi , Mehdi Amiri-Aref

{"title":"A distributionally robust optimisation with joint chance constraints approach for location-routing problem in urban search and rescue operations","authors":"Kamran Sarmadi , Mehdi Amiri-Aref","doi":"10.1016/j.cor.2025.107051","DOIUrl":"10.1016/j.cor.2025.107051","url":null,"abstract":"<div><div>This paper examines a multi-period location-routing problem with uncertain demand and travel times in the context of disaster management. We propose an optimisation model that integrates strategic location decisions with multi-period routing decisions to navigate search-and-rescue teams in the aftermath of a disaster within an uncertain environment. To model this problem, we apply a distributionally robust optimisation approach with joint chance constraints. We enhance computational tractability by reformulating the problem using Bonferroni’s inequality and approximating the chance constraints. The proposed methodology is evaluated in a hypothetical case study of Santa Cruz County, California, USA, a region highly susceptible to earthquakes. We tested multiple instances of this case study to demonstrate the effectiveness of the proposed method compared to the sample average approximation approach. Numerical experiments reveal that the methodology developed in this paper aids decision-makers in strategically locating facilities to deploy search-and-rescue teams and efficiently directing them towards affected sites, achieving a maximal rescue rate.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107051"},"PeriodicalIF":4.1,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Periodic and aperiodic train timetabling and rolling stock circulation planning using an efficient Lagrangian relaxation decomposition

IF 4.1 2区工程技术

Computers & Operations Research Pub Date : 2025-03-18 DOI: 10.1016/j.cor.2025.107062

Naijie Chai , Ziyu Chen , Wenliang Zhou

{"title":"Periodic and aperiodic train timetabling and rolling stock circulation planning using an efficient Lagrangian relaxation decomposition","authors":"Naijie Chai , Ziyu Chen , Wenliang Zhou","doi":"10.1016/j.cor.2025.107062","DOIUrl":"10.1016/j.cor.2025.107062","url":null,"abstract":"<div><div>Train timetabling and rolling stock circulation planning are problems of crucial importance for integrated planning. Often, these problems are separately solved in a sequential way without consideration of periodic train schedule. However, a notable drawback of this layered planning process is poor coordination and efficiency between train and rolling stock timetables, as well as lack of regularity. To this end, we explore the joint optimization problem of periodic and aperiodic train timetabling and rolling stock circulation planning in this paper. To address this comprehensive problem, an integer programming model is initially established by incorporating rolling stock circulation into optimizing periodic and aperiodic train timetabling. Due to the model-solving complexity, a three-dimensional space–time-state network is constructed to reformulate this model. Within this three-dimensional network, states are used to represent trains served by rolling stocks. Subsequently, the problem is transformed into a minimum-cost multi-commodity network flow problem with incompatible arcs based on the space–time-state network. And an efficient Lagrangian relaxation decomposition algorithm is proposed to solve this network flow problem. The effectiveness of the algorithm is verified through a series of case studies.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"180 ","pages":"Article 107062"},"PeriodicalIF":4.1,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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