检索结果-内蒙古大学图书馆

Integrated demand-oriented and energy-efficiency train timetabling and rolling stock circulation planning for an urban rail transit line

引用

TRANSPORTATION REsearch PART C-EMERGING TECHNOLOGIES 2025年 171卷

作者： Huang, Yu Zhou, Wenliang Xu, Guangming Deng, Lianbo Cent South Univ Sch Traff & Transportat Engn Changsha 410000 Hunan Peoples R China

Saving energy has both significant environmental benefits and economic advantages. As the urban rail transit network and its consumed energy continue to expand, it is crucial to optimize the energy-saving operation scheme of trains. Energy-saving train operation often requires longer section running times, which is obviously not conducive to the quality of passenger service. In order to ensure passenger service quality when pursuing the decrease of the train's energy consumption and rolling stocks' operation cost, this paper proposes an integrated optimization model of the demand-oriented and energy-efficiency train timetable and rolling stock circulation plan for urban rail transit. Its objective is to minimize train net energy consumption, rolling stock utilization cost, as well as passenger waiting time and travel time. Specifically, the net energy consumption is defined as the difference between train required traction energy consumption and regenerative braking energy utilization. To efficiently solve this large-scale mixed integer nonlinear model, we design a solution algorithm combining variable neighborhood search (VNS) and CPLEX, in which seven different neighborhood structures are constructed. Based on the data of Guangzhou Metro Line 13, we have verified the effectiveness and performance of the model and algorithm through numerical experiments of various scales, as well as through comparisons with other algorithms and models. The results demonstrate that the timetable and rolling stock circulation plan obtained by VNS can reduce net energy consumption by 9.55 %, rolling stock utilization cost by 9 %, and passenger waiting time by 4.77 %, and their travel time by 0.87 % compared to the current timetable.

关键词： Urban rail transit line Demand-oriented energy-efficiency train time tabling Rolling stock circulation planning Train traction energy Regenerative braking energy variable neighborhood search algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal experimental plan for multi-level stress testing with log-location-scale regression under progressive Type-II censoring

引用

QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT 2025年

作者： Lin, Chien-Tai Li, Yun-Wei Chen, Zhi-Wei Bhattacharya, Ritwik Tamkang Univ Dept Math 151 Yingzhuan Rd New Taipei City 251301 Taiwan Univ Texas El Paso Dept Math Sci El Paso TX USA

We examine the optimal allocation strategy based on a general Type-II progressively censored sample within the framework of a multi-level stress log-location-scale regression model. To identify the optimal censoring schemes, we propose employing a meta-heuristic algorithm rooted in the variable neighborhood search (VNS) approach. Our findings reveal that the VNS-based procedure not only significantly reduces the search time but also achieves the exact optimal allocation and progressive censoring schemes for small sample sizes as those derived from exhaustive search methods. Additionally, for larger sample sizes, the procedure attains optimal or near-optimal objective values within a reasonable computational time. The effectiveness of optimal unit allocation in multi-level stress experiments is illustrated through a real-world data set concerning hardened steel specimens in a rolling contact fatigue test.

关键词： Constant-stress life-testing log-location-scale distribution optimal criteria variable neighborhood search algorithm

来源：评论

学校读者我要写书评

暂无评论

A novel mathematical modeling approach for integrating a periodic vehicle routing problem and cross-docking system

引用

COMPUTERS & OPERATIONS REsearch 2025年 180卷

作者： Asgharyar, Mostafa Farmand, Nima Shetab-Boushehri, Seyyed Nader Isfahan Univ Technol Dept Ind & Syst Engn Esfahan *** Iran

To remain competitive in a globalized market, manufacturers must effectively respond to customer demands in various situations. In parallel, logistics companies have adopted cross-docking systems as a key component of lean supply chain management to handle high transportation volumes. By integrating this pivotal component in the supply chain, goods are efficiently distributed to retailers via cross-dock facilities. This article introduces, for the first time, an integrated framework for the periodic vehicle routing problem with cross-docking (PVRPCD) system between supplier and retailer locations. The goal is to optimize three key decisions: 1. Vehicle scheduling and routing for each period, 2. The loading and unloading quantities of goods at the cross-dock, and 3. The selection of a daily combination from periodic retailer demands to minimize the costs incurred by transportation and cross-docking operations. To formulate the PVRPCD, a novel mixed-integer linear programming (MILP) model is designed. Given the computational complexity of large-scale instances, a heuristic algorithm is designed to produce near-optimal initial solutions, which are then embedded into two metaheuristic algorithms: variable neighborhood search (VNS) and population-based variable neighborhood search (PBVNS). These algorithms incorporate four shaking and four local search operators to enhance solution quality and scalability. To validate the effectiveness of the metaheuristic algorithms, computational experiments are conducted using benchmark instances. The optimal solutions obtained via the CPLEX solver for small-scale instances serve as a baseline for comparison. The computational results illustrate that both algorithms effectively solve small-scale problems. Nevertheless, PBVNS consistently outperforms VNS in terms of solution quality, though it requires more computation time. Despite the increased solution time, the improvement in solution quality justifies the additional computational

关键词： Periodic vehicle routing problem Cross-docking Multiple demands Mathematical programming Heuristic algorithm variable neighborhood search algorithm

来源：评论

学校读者我要写书评

暂无评论

Collaborative optimization for scheduling manufacturing tasks and transport vehicles considering manufacturer's time availability in cloud manufacturing

引用

INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2024年第6期38卷 818-843页

作者： Zhao, Zian Zhou, Hong Zheng, Weibo Beihang Univ Sch Econ & Management 37 Xueyuan Rd Beijing 100191 Peoples R China Beihang Univ Beijing Key Lab Emergency Support Simulat Technol Beijing Peoples R China China Aerosp Standardizat Inst Beijing Peoples R China

As an advanced networked intelligent manufacturing model, cloud manufacturing (CMfg) effectively integrates available resources by strengthening the connection among various manufacturers to solve complex manufacturing problems. Due to the geographical dispersion of manufacturers and the cooperativity nature of the manufacturing process, logistic impacts are non-negligible in scheduling. This paper focuses on the collaborative scheduling of manufacturing and transportation services. To make full use of the manufacturer's capacity without affecting his benefit, local tasks are scheduled with higher priority on a manufacturer while the service time for CMfg tasks is assumed to be fragmented and represented as a set of available time windows. Based on these considerations, a collaborative optimization model for CMfg on task and vehicle scheduling with manufacturing service windows is established, in which the completion time of all CMfg orders and the total idle traveling time of vehicles are minimized to ensure the efficiency of both manufacturing and logistic service. A dual-loop variable neighborhood search algorithm is designed to solve the problem. Comprehensive experiments are conducted, showing improvements of 2.41% to 29.57% in objective and fewer vehicles needed compared with some existing methods, which validate the efficacy of the proposed model and method.

关键词： Cloud manufacturing scheduling vehicle scheduling collaborative optimization time window variable neighborhood search algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal life-testing plans for joint progressively Type-II censored Birnbaum-Saunders distributions with compound optimal criteria

引用

QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT 2024年第4期22卷 605-630页

作者： Lin, Chien-Tai Chen, Zhi-Wei Li, Yun-Wei Ng, Hon Keung Tony Tamkang Univ Dept Math New Taipei City 25137 Taiwan Bentley Univ Dept Math Sci Waltham MA USA

In this paper, we first derive the maximum likelihood estimates (MLEs) of the parameters of Birnbaum-Saunders (BISA) distributions based on the joint progressive Type-II censored (JPC) samples. We also discuss using the EM algorithm to obtain the MLEs of the model parameters. Then, we determine the single-objective-criterion optimal JPC schemes for BISA distributions based on the cost minimization criterion, $A$A-optimality criterion, and $D$D-optimality criterion by the complete search method, variable neighborhood search (VNS) algorithm and modified VNS (MVNS) algorithm. These algorithms are compared in terms of accuracy and computation time. In addition, we determine the compound-criterion optimal JPC schemes based on different optimal criteria and the reasonably efficient compound optimal JPC schemes for two competing statistical models, such as the inverse Gaussian and BISA models. The advantages of using the compound optimal scheme over the single-objective-criterion optimal scheme are demonstrated through a real-life data set on the micro-indentation test about the hardness of polymeric bone cement.

关键词： EM algorithm maximum likelihood estimation Monte Carlo simulation optimal criteria variable neighborhood search algorithm

来源：评论

学校读者我要写书评

暂无评论

Hybrid artificial immune algorithm for energy-efficient distributed flexible job shop in semiconductor manufacturing

引用

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2024年第3期27卷 3075-3098页

作者： Chen, Xiaolong Du, Yu Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China HengXing Univ Sch Informat Engn Qingdao Peoples R China Univ Jinan Sch Informat Sci & Engn Jinan 250022 Peoples R China

In semiconductor manufacturing, constraints, including multiple scheduling routes, complex production processes, and robotic transportation, particularly bring difficult challenges to production schedules. To address this issue, we investigated an energy-efficient distributed flexible job shop scheduling problem with robotic transportation. In the considered problem, two objectives, i.e., the maximum completion time and total energy consumption, are minimized simultaneously. First, two mixed integer linear programming models are constructed, including the sequence-based and position-based models. Then, a hybrid algorithm combining the artificial immune algorithm and variable neighborhood search algorithm is proposed. To generate a population with better performance and diversity, five initialization strategies and an active decoding method are designed. In addition, a novel clone mechanism and an improved suppression process are being developed to improve the exploration abilities. Furthermore, two distinct neighborhood structures and two object-oriented local search heuristics are designed to balance exploration and exploitation capabilities. Eventually, the proposed algorithm achieved better performance with the comparison of three other state-of-the-art algorithms with different scale instances.

关键词： Distributed flexible job shop scheduling problem Robotic transportation Mixed integer linear programming models Artificial immune algorithm variable neighborhood search algorithm

来源：评论

学校读者我要写书评

暂无评论

A MULTI-OBJECTIVE APPROACH TO HOME HEALTH CARE ROUTING PROBLEM WITH TEAM FORMATION

引用

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2023年第5期30卷 1150-1168页

作者： Bektur, Gulcin Nenbhard, David Univ Iowa Dept Ind & Syst Engn Iowa City IA 52242 USA Iskenderun Tech Univ Dept Ind Engn Hatay Turkiye Harvey Mudd Coll Dept Engn Claremont CA 91711 USA

Home health care (HHC) services provide the elderly, disabled, and those with chronic diseases health services in their homes. The demand for HHC services has increased due to the growth of the elderly population, the increase in hospital occupancy rates during the pandemic, and developments in medical device technologies. In this study, team formation is taken into consideration in a multi-period and multi-objective HHC assignment, scheduling and routing problem. The team and the assigned patients to this team must be compatible with skill levels and operational requirements. The objective functions are minimization of total completion time and maximum working time overall caregivers. To evaluate our approach, an HHC service unit in a state hospital is adopted as the operational scenario, and we propose a multi-objective mathematical model to solve the problem. In this model, HHC teams are formed, the patients are assigned to the teams, and the route of each team is determined in an integrated manner. The variable neighborhood search algorithm is modified to solve the multi-objective optimization model and is improved with a local search algorithm. The proposed algorithm has been compared with the stateof-the-art multi-objective algorithms in the literature over test problems. Current results show that the model to be an effective means of estimating and predicting system behavior in this complex environment.

关键词： home health care routing problem team formation multi-period multi-objective mathematical model variable neighborhood search algorithm

来源：评论

学校读者我要写书评

暂无评论

A variable Group Parallel Flexible Job Shop Scheduling in a SMEs Manufacturing Platform

引用

IEEE ACCESS 2023年 11卷 79531-79541页

作者： Choi, Yeonjee Hwang, Hyun Suk Kim, Chang Soo Pukyong Natl Univ Dept Informat Syst Busan 608737 South Korea Hanyoung DS Inc Res Ctr Seoul 07600 South Korea

Manufacturing is a broad field with different types of production processes. Therefore, specific processes can accommodate multiple parallel machines operating simultaneously in some production environments. This assumption is particularly crucial in factory scheduling for industries such as textile, aircraft, and semiconductor manufacturing. The assumption proposed in this paper is differ from FJSP in that they are closer to the real world by allowing different machines to perform the same multiple processes. In this paper, a new approach for solving the flexible job shop scheduling problem has been proposed, which is referred to as the flexible job shop scheduling problem in a parallel machine environment with a variable group. We proposed a hybrid genetic algorithm-based variable neighborhood search algorithm (GA-VNS) to solve this problem, where the multiple parallel machines can operate the same operations simultaneously and are grouped as a variable group. The GA-VNS algorithm combines the global searching ability of GA with the local searching ability of VNS to fully reflect the condition of the parallel machines with variable groups. The objective functions of the algorithm are to minimize the production makespan and to improve facility usage. Multiple simulation experiments are conducted using forty-seven test instances to assess the feasibility and effectiveness of the new approach. This study is expected to reduce processing time and production costs for Small and Medium Enterprises (SMEs) with low cost and high efficiency compared to existing systems, such as the manufacturing execution system, enterprise resource planning, and job shop scheduling system.

关键词： Genetic algorithms variable neighborhood search algorithm flexible job shop scheduling problem global and local searching algorithm parallel machines small and medium sized enterprises manufacturing platform

来源：评论

学校读者我要写书评

暂无评论

A novel robust model for location-allocation of healthcare facilities considering pre-disaster and post-disaster characteristics

引用

SCIENTIA IRANICA 2023年第2期30卷 619-641页

作者： Alinaghian, M. Hejazi, S. R. Bajoul, N. Velni, K. Sadeghi Isfahan Univ Technol Dept Ind & Syst Engn Esfahan *** Iran Univ Tehran Fouman Fac Engn Dept Ind Engn Fouman Iran

Healthcare centers are one of the most important municipal facilities that are responsible for providing personal and social health. Locating medical centers is an important strategy to improve the performance of these facilities and reduce any delay in the relief process. During disasters, these centers play a critical role in reducing the risk of human casualties. In this regard, the current study aims to establish a new robust mathematical model to simultaneously locate and allocate healthcare facilities, including different levels of medical care services, considering the characteristics in normal and disaster situations. Further, to help victims and prevent overcrowding at medical centers during disasters, establishment of temporary and outpatient centers was suggested for emergency provision of basic services. In addition, the possibility of delivering the needed equipment and medical teams to these centers was incorporated in the proposed modeling. To solve the problem, two metaheuristic algorithms, harmony search algorithm and hybrid tabu search combined with variable neighborhood search algorithm, and a lower bound based on Lagrangian relaxation method were employed. To assess the performance of the proposed algorithms, sample problems were randomly generated. The results obtained from the exact solutions and lower bound from the Lagrangian relaxation method were compared with those from the meta-heuristic algorithms, confirming the good performance of the proposed algorithms. (c) 2023 Sharif University of Technology. All rights reserved.

关键词： Health management system Network reliability Hierarchical healthcare facility Location problem Robust optimization variable neighborhood search algorithm Harmony search algorithm

来源：评论

学校读者我要写书评

暂无评论

A simulation-based metro train scheduling optimization incorporating multimodal coordination and flexible routing plans

引用

TRANSPORTATION REsearch PART C-EMERGING TECHNOLOGIES 2023年 146卷

作者： Wang, Xingrong Lv, Ying Sun, Huijun Xu, Guangtong Qu, Yunchao Wu, Jianjun Beijing Jiaotong Univ Inst Transportat Syst Sci & Engn Key Lab Transport Ind Big Data Applicat Technol Co Minist Transport Beijing 100044 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China

The promotion of multimodal coordination is of great significance to the joint development of diversified urban transportation systems. Focusing on an urban comprehensive passenger trans-port hub (UCPTH) that converges both inter-city modes and multiple inner-city modes, this study aims to customize a bridging metro train operation plan with the utilization of multimodal passenger simulation. A bi-objective integer nonlinear programming model (INLP) incorporating train schedule and flexible routing plan is proposed to minimize passenger waiting time and operating costs simultaneously. Notably, a real-time flow prediction method based on Monte Carlo simulation and queuing network system is proposed and embedded in the optimization model framework to reflect the difference of individual passengers' transfer walking time and thereby provide detailed passenger distribution on the platform for metro hub stations connecting UCPTH. Compared with the estimation using historical data, this method can particularly support the scheduling coordination of metro and other modes during an abrupt change of arrival flows. Moreover, to solve the collaborative optimization model tractably, the epsilon-constraint method based on a tailored variable neighborhood search algorithm is developed to generate approximate Pareto optimal solutions, including the number of effective trains, demand-sensitive headway, the route pattern of each effective train, and train dwell time. Finally, two sets of numerical exper-iments, including a small-scale case and a real-world hub-metro network instance are conducted to demonstrate the effectiveness of the proposed approaches. The study associated with the findings can benefit both metro providers and users especially those who need to transfer to the metro system at hubs by achieving the best match between passenger and train flows in temporal and spatial domains.

关键词： Metro train schedule Multimodal coordination Flexible routing plans Passenger simulation variable neighborhood search algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：