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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Now showing 1 - 10 of 34

An Intelligent Elevator Development and Management System
(2020-06-01)
Van, Lan-Da
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Lin, Yi-Bing
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Wu, Tsung-Han
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Lin, Yu-Chi
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資訊工程學系
This paper proposes ElevatorTalk, an elevator development and management system based on the Internet of Things (IoT) approach called IoTtalk. This system modularizes the software into elevator components so that we can develop flexible and scalable car scheduling algorithms. ElevatorTalk consists of three subsystems: cars, scheduler, and the elevator car operating (ECO) panel. The first two subsystems are used to develop the elevator systems, and the third subsystem is used to receive requests issued by the passengers. These three subsystems work in parallel, and communicate with each other through sending and receiving messages. ElevatorTalk can connect to a real elevator system to serve as the elevator management center. It can also emulate the existing elevator systems with different car scheduling algorithms. We propose an intelligent aggressive car scheduling with initial car distribution (ACSICD) algorithm in ElevatorTalk. Our paper indicates that ACSICD has better waiting/travel/journey time performance and/or accuracy than the previous proposed algorithms. We also show that in our approach, the car scheduling decision can be quickly made with 0.2010 ms, and therefore good performance in the time complexity is achieved.
Minimizing machine assignment costs over Delta-approximate solutions of the scheduling problem P parallel to C-max
(2019-11-12)
Kononov, A. V.
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Kovalyov, M. Y.
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Lin, B. M. T.
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
Bi-criteria lexicographical minimization problems with the makespan as the primary objective and the total machine assignment costs as the secondary objective have been recently introduced to the scheduling research, and polynomial time (r + 1, 1)-approximation algorithms have been suggested for their solution, where 1 < r < 2 is the performance ratio of an approximation algorithm for P parallel to C-max. We improve these results by presenting a polynomial time (1.5r - 1, 1)-approximation algorithm for the additive cost type. Then, we introduce a problem of minimizing the total machine assignment cost over the Delta-approximate solutions of the makespan minimization problem. We prove that this new problem is strongly NP-hard and pseudo-polynomially non-approximable in general. A polynomial time approximation algorithm with a guaranteed approximation ratio is presented for the additive cost type and bounded ratio between the maximal and minimal machine costs. An O (mn(2k)) time dynamic programming algorithm is also presented, where k is the fixed number of distinct job processing times. (C) 2019 Elsevier B.V. All rights reserved.
Minimizing the Sum of Makespan and Total Weighted Tardiness in a No-Wait Flowshop
(2018-01-01)
Lin, Shih-Wei
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Lu, Chung-Cheng
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Ying, Kuo-Ching
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper presents a cloud theory-based iterated greedy (CTIG) algorithm for solving the no-wait flowshop scheduling problem (NWFSP) with the objective of minimizing the sum of makespan and total weighted tardiness. The performance of the proposed CTIG algorithm is evaluated by comparing its computational results to those of the best-to-date meta-heuristic algorithm, particle swarm optimization (PSO), as presented in this paper. The experimental results concerning two sets of benchmark problem instances in this paper demonstrate that the CTIG algorithm obtains more (near) optimal solution in less computational time than the PSO algorithm. The computational results in this paper fill the research gap in the development of a novel algorithm to improve the solution quality in the case of the NWFSP with the objective of minimizing the sum of makespan and total weighted tardiness.
Optimal multiple-period scheduling and sequencing of operating room and intensive care unit
(2018-10-01)
Al-Refaie, Abbas
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Judeh, Mays
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Chen, Toly
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工業工程與管理學系
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Department of Industrial Engineering and Management
Operating rooms (ORs), one of the most crucial hospital resources that generate among the highest costs, are prone to bottlenecking. This paper, therefore, proposes optimization models for multiple-period scheduling of patients in ORs and intensive care units (ICUs) as well as for sequencing of patients in the operating theatre. The first model considers scheduling at a minimal total cost, comprising hospitalization, undertime, overtime, and cancelation costs. The second model involves ICU scheduling and patient sequencing in the operating theatre at a minimal total overtime cost. The scheduling and sequencing models were implemented at a hospital that offers comprehensive surgical procedures for all surgical specialties. The research results are expected to improve patient satisfaction and resource efficiency as well as reduce hospital expenses by minimizing overtime, undertime, hospitalization costs, and cancelation costs. These optimization models may provide substantial assistance to decision makers and planners in facilitating coordination among available hospital resources, including ORs, surgeons, and patients, thereby increasing the productivity and efficiency of ORs and ICUs in providing high-quality care. Future research should consider OR scheduling for unexpected events.
Optimal scheduling of a taxi fleet with mixed electric and gasoline vehicles to service advance reservations
(2018-08-01)
Lu, Chung-Cheng
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Yan, Shangyao
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Huang, Yu-Wei
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
This study addresses the problem of scheduling a fleet of taxis that are appointed to solely service customers with advance reservations. In contrast to previous studies that have dealt with the planning and operations of a taxi fleet with only electric vehicles (EVs), we consider that most taxi companies may have to operate with fleets comprised of both gasoline vehicles (GVs) and plug-in EVs during the transition from GV to (complete) EV taxi fleets. This paper presents an innovative multi-layer taxi-flow time-space network which effectively describes the movements of the taxis in the dimensions of space and time. An optimization model is then developed based on the time-space network to determine an optimal schedule for the taxi fleet. The objective is to minimize the total operating cost of the fleet, with a set of operating constraints for the EVs and GVs included in the model. Given that the model is formulated as an integer multi-commodity network flow problem, which is characterized as NP-hard, we propose two simple but effective decomposition-based heuristics to efficiently solve the problem with practical sizes. Test instances generated based on the data provided by a Taiwan taxi company are solved to evaluate the solution algorithms. The results show that the gaps between the objective values of the heuristic solutions and those of the optimal solutions are less than 3%, and the heuristics require much less time to obtain the good quality solutions. As a result, it is shown that the model, coupled with the algorithms, can be an effective planning tool to assist the company in routing and scheduling its fleet to service reservation customers.
Improved Exact Methods for Solving No-Wait Flowshop Scheduling Problems With Due Date Constraints
(2018-01-01)
Ying, Kuo-Ching
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Lu, Chung-Cheng
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Lin, Shih-Wei
;
運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
The no-wait flowshop scheduling problem with hard due date constraints is critical to operations in many industries, such as plastic, chemical, and pharmaceutical manufacturing. However, to date, there is a lack of effective optimization algorithms for this NP-hard problem. This paper develops a new mixed integer linear programming (MILP) model and a two-phase enumeration algorithm to improve the best-so-far exact methods for solving this problem with the objective of minimizing the makespan. A comprehensive computational experiment is performed to compare the performances of the discussed exact methods. The computational results demonstrate that the proposed MILP model and the two-phase enumeration algorithm significantly outperform the best-so-far optimization methods, and the (sub-) optimal solutions to several unsolved instances from the literature are reported.
Effects of different chromosome representations in developing genetic algorithms to solve DFJS scheduling problems
(2017-04)
Wu, Muh-Cherng
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Lin, Chi-Shiuan
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Lin, Chia-Hui
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Chen, Chen-Fu
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工業工程與管理學系
This paper attempts to compare the effect of using different chromosome representations while developing a genetic algorithm to solve a scheduling problem called DFJS (distributed flexible job shop scheduling) problem. The DFJS problem is strongly NP-hard; most recent prior studies develop various genetic algorithms (GAs) to solve the problems. These prior GAs are similar in the algorithmic flows, but are different in proposing different chromosome representations. Extending from this line, this research proposes a new chromosome representation (called Sop) and develops a genetic algorithm (called GA_OP) to solve the DFJS problem. Experiment results indicate that GA_OP outperforms all prior genetic algorithms. This research advocates the importance of developing appropriate chromosome representations while applying genetic algorithms (or other meta-heuristic algorithms) to solve a space search problem, in particular when the solution space is high-dimensional. (C) 2016 Elsevier Ltd. All rights reserved.
Exact algorithms for single-machine scheduling problems with a variable maintenance
(2016-08)
Ying, Kuo-Ching
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Lu, Chung-Cheng
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Chen, Jhao-Cheng
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper deals with four single-machine scheduling problems (SMSPs) with a variable machine maintenance. The objectives of the four SMSPs are to minimize mean lateness, maximum tardiness, total flow time and mean tardiness, respectively. These four SMSPs are important in the literature and in practice. This study proposes an exact algorithm with the computational complexity O(n(2)) for each of the four SMSPs. In addition to the given jobs, the machine maintenance activity between two consecutive jobs is optimally scheduled. (C) 2016 Elsevier Ltd. All rights reserved.
TALENT HOLD COST MINIMIZATION IN FILM PRODUCTION
(2017-01)
Cheng, Tai Chiu Edwin
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Lin, Bertrand Miao-Tsong
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Huang, Hsiao-Lan
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
This paper investigates the talent scheduling problem in film production, which is known as rehearsal scheduling in music and dance performances. The first lower bound on the minimization of talent hold cost is based upon the outside-in branching strategy. We introduce two approaches to add extra terms for tightening the lower bound. The first approach is to formulate a maximum weighted matching problem. The second approach is to retrieve structural information and solve a maximum weighted 3-grouping problem. We make two contributions: First, our results can fathom the matrix of a given partial schedule. Second, our second approach is free from the requirement to schedule some shooting days in advance for providing anchoring information as in the other approaches, i.e., a lower bound can be computed once the input instance is given. The lower bound can fit different branching strategies. Moreover, the second contribution provides a state-of-the-art research result for this problem. Computational experiments con firm that the new bounds are much tighter than the original one.
Acquisition planning and scheduling of computing resources
(2016-12)
Yang, Chien-Nan
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Lin, Bertrand M. T.
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Hwang, F. J.
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Wang, Meng-Chun
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資訊管理與財務金融系註：原資管所+財金所
Cloud computing has been attracting considerable attention since the last decade. This study considers a decision problem formulated from the use of computing services over the Internet. An agent receives orders of computing tasks from his/her clients and on the other hand he/she acquires computing resources from computing service providers to fulfill the requirements of the clients. The processors are bundled as packages according to their speeds and the business strategies of the providers. The packages are rated at a certain pricing scheme to provide flexible purchasing options to the agent. The decision of the agent is to select the packages which can be acquired from the service providers and then schedule the tasks of the clients onto the processors of the acquired packages such that the total cost, including acquisition cost and scheduling cost (total weighted tardiness), is minimized. In this study, we present an integer programming model to formulate the problem and propose several solution methods to produce acquisition and scheduling plans. Ten well-known heuristics of parallel-machine scheduling are adapted to fit into the studied problem so as to provide initial solutions. Tabu search and genetic algorithm are tailored to reflect the problem nature for improving upon the initial solutions. We conduct a series of computational experiments to evaluate the effectiveness and efficiency of all the proposed algorithms. The results of the numerical experiments reveal that the proposed tabu search and genetic algorithm can attain significant improvements. (C) 2016 Elsevier Ltd. All rights reserved.

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