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Determining a subsidy rate for Taiwan's recycling glass industry: an application of bi-level programming

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2012年第1期63卷 28-37页

作者： Shih, H-S Cheng, C-B Wen, U-P Huang, Y-C Peng, M-Y Tamkang Univ Dept Informat Management Taipei 25137 Taiwan Tamkang Univ Grad Inst Management Sci Taipei 25137 Taiwan Natl Tsing Hua Univ Hsinchu Taiwan

This study attempts to optimize the operations of the Recycling Fund Management Board (RFMB), founded by the Environmental Protection Administration of the R.O.C. Government (on Taiwan), through the decision of a subsidy rate for the domestic glass recycling industry. The hierarchical and interactive nature between the two parties is modelled by bi-level programming, where the RFMB plays the upper-level decision unit while the recycling industry is the lower-level counterpart. In order to solve the problem by optimization software, the bi-level formulation is transformed to a single-level problem via Karush-Kuhn-Tucker optimality conditions and is further transformed to a 0-1 mixed integer programming problem by variable substitution. The problem is solved with real-world data, and the obtained solutions are analysed and compared with the RFMB's current operations. The results suggest that the proposed approach can improve the operations of the RFMB. Journal of the Operational Research Society (2012) 63, 28-37. doi:10.1057/jors.2011.13 Published online 30 March 2011

关键词： bi-level programming problem glass recycling industry subsidy rate recycling and treatment fee 0-1 mixed integer programming KKT conditions

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Multi-step methods for choosing the best set of variables in regression analysis

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2010年第3期46卷 417-426页

作者： Konno, Hiroshi Takaya, Yoshihiro Chuo Univ Dept Ind & Syst Engn Tokyo 112 Japan

In a recent article (Konno and Yamamoto in ISE 07-01, Department of Industrial and Systems Engineering, Chuo University, February 2007), one of the authors formulated the problem of choosing the best set of explanatory variables from a large number of candidate variables in a linear regression model as a mixed 0-1 integer linear programming problem and showed that it can be solved by the state-of-the-art integer programming software. In this paper, we will propose multi-step methods for calculating a close to optimal solution of the problem which may not be solved by a single-step method presented in Konno and Yamamoto (ISE 07-01, Department of Industrial and Systems Engineering, Chuo University, February 2007). It will be shown that a multi-step method can generate a nearly optimal solution within a fraction of computation time of the single step method. Also, we will demonstrate that the best set of variables in terms of the squared error can be recovered under normality assumption.

关键词： Linear regression model Variable selection 0-1 mixed integer programming Least absolute deviation fitting

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Lagrange relaxation decomposition for synchronized production and transportation planning with flexible vehicles

Lagrange relaxation decomposition for synchronized productio...

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International Conference on Service Systems and Service Management

作者： Tang, JF Yung, KL Liu, SX Northeastern Univ Sch Informat Sci & Engn MOE Key Lab Proc Automat Ind Liaoning 110004 Peoples R China

ISBN: (纸本)0780389719

Effective management of interfaces between procurement, supply, production and distribution as a whole towards higher efficiency of supply chain is an important issue in a global manufacturing environment, where coordination of production and distribution particularly synchronization of production and transportation planning becomes an important savings in operational costs. A synchronized production and transportation planning for a production distribution network is discussed in this paper. In the production-distribution network, transportation business is subcontracted to professional transportation enterprise (PTE), e.g. 3PL in a vehicle-rent way. The problem addressed tries to determine not only the synchronized schedule of production and transportation (when and in what quantity each product is produced and for alignment with the shipment), but also the number of vehicles required towards minimum total costs of production set-up, inventory, transportation and rent costs in vehicles over the planning horizon. A non-linear 0-1 mixed integer programming is developed and a Lagrange relaxation decomposition method is proposed.

关键词： Lagrange Relax Decomposition synchronization, production and transportation network 0-1 mixed integer programming

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A maximal predictability portfolio using absolute deviation reformulation

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COMPUTATIONAL MANAGEMENT SCIENCE 2010年第1期7卷 47-60页

作者： Konno, Hiroshi Morita, Yuuhei Yamamoto, Rei Chuo Univ Dept Ind & Syst Engn Tokyo Japan Mitsubishi UFJ Trust Investment Technol Inst Co L Tokyo Japan

This paper shows that a large-scalemaximal predictability portfolio (MPP) optimization problem can be solved within a practical amount of computational time using absolute deviation instead of squared deviation in the definition of the coefficient of determination. Also, we will show that MPP portfolio outperforms the mean-absolute deviation portfolio using real asset data in Tokyo Stock Exchange.

关键词： Portfolio optimization Maximal predictability portfolio Absolute deviation Fractional programming 0-1 mixed integer programming

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Checking existence of tolerance solutions of interval linear equations via mixed integer progrmming

Checking existence of tolerance solutions of interval linear...

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3rd International Conference on Manufacturing Science and Engineering (ICMSE 2012)

作者： Wang, Huping Li, Wei Wang, Qin Zhao, Zhili Hangzhou Dianzi Univ Inst Operat Res & Cybernet Hangzhou 310018 Zhejiang Peoples R China China Jiliang Univ Coll Sci Hangzhou 310018 Peoples R China

ISBN: (纸本)9783037853726

An approach to deal with interval linear equations is to reduce the problem into solving several linear (or nonlinear) equations (or inequalities). To obtain characterations of the equations the paper gives a necessary condition of tolerance solutions of interval linear equations by means of nonlinear inequalities. Based on the necessary condition, a sufficience condition for nonexistence of tolerance solutions of the equations is given by use of the well-known Farkas theorem.

关键词： Interval linear equations 0-1 mixed integer programming tolerance solutions Farkas theorem

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Improvement of job shop scheduling method based on mathematical optimization and machine learning 5

Improvement of job shop scheduling method based on mathemati...

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5th International Conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Morinaga, Eiji Tang, Xuetian Iwamura, Koji Hirabayashi, Naoki Osaka Metropolitan Univ I-1 GakuenchoNaka Ku Sakai Osaka 5998531 Japan Osaka Prefecture Univ I-1 GakuenchoNaka Ku Sakai Osaka 5998531 Japan Sharp Co Ltd Sakai Osaka Japan

This research is concerned with finding the optimal solution of a job shop scheduling problem (JSSP) in a shorter time. As a result of recent trends such as Industry 4.0, machine learning has received a lot of attention, and job shop scheduling methods using machine learning techniques have been developed. We have focused on hybridization of machine learning and mathematical optimization. A JSSP can be formulated as a 0-1 mixed integer programming, and it is expected that the optimal solution can be obtained in a shorter time by providing a good initial solution for the optimization algorithm by means of a learner constructed with data of scheduling performed previously. In our method based on this idea, the processing times of all operations are used as input features to predict a good value of each binary variable which represents the precedence relationship between two operations processed on the same machine. However, the information about the operations which are not related to the intended two operations may work as noise in learning and prediction. In this paper, two limitation methods of input features are proposed. In one of the methods, the processing times of only the operations processed on the same machine that the intended operations are processed are input to the learner. In the other methods, the processing times of those operations and their pre/post operations are input. Numerical experiments showed that these methods are effective at least from the point of view of efficient construction of a learner, because the number of nodes in the input and hidden layers can be reduced. From the aspect of better learning and prediction, both of the methods worked well, that is, they could find the optimal solution in a shorter time than the previous method in the cases where the previous method could not achieve good prediction and took a relatively long solution time. However, in the cases where the previous method could solve the problem in a relatively sho

关键词： Data-driven job shop scheduling 0-1 mixed integer programming Multilayer neural network Input feature Solution time

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Study on Manufacturing Enterprises Distribution Center Location

Study on Manufacturing Enterprises Distribution Center Locat...

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3rd International Conference on Materials and Products Manufacturing Technology (ICMPMT 2013)

作者： Ji, Shouwen Huang, Tingting Zhang, Yunfeng Beijing Jiaotong Univ Sch Traff & Transportat Beijing Peoples R China Shenyang Jianzhu Univ Sch Transportat & Municipal Engn Shenyang Peoples R China

ISBN: (纸本)9783037859162

The problem of one-level distribution centers is researched in this paper. It is a customer-oriented problem. This paper is from the perspective of manufacturing enterprises. The assumed conditions about location are put forward. The costs associated with distribution center location are analyzed. Distribution center location model is built by 0-1 mixed integer programming. And the software LINGO is used to solve the model. Distribution center location algorithm is verified by an example in the paper. The example explains that combining 0-1 mixed integer programming with LINGO is simple and effective to distribution center location.

关键词： Manufacturing Enterprises Distribution Center Location 0-1 mixed integer programming LINGO

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AN IMPROVED METHOD FOR JOB SHOP SCHEDULING BY MEANS OF MACHINE LEARNING AND MATHEMATICAL OPTIMIZATION

AN IMPROVED METHOD FOR JOB SHOP SCHEDULING BY MEANS OF MACHI...

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International Symposium on Flexible Automation (ISFA)

作者： Morinaga, Eiji Oda, Atsuya Osaka Metropolitan Univ Osaka Japan Osaka Prefecture Univ Osaka Japan

ISBN: (纸本)9780791887882

This paper is concerned with solving a job shop scheduling problem (JSSP) optimally in a shorter time by predicting a good solution based on a database of scheduling performed previously and then providing it as an initial solution in the optimization algorithm. Although several methods based on this framework have been developed, they have a problem that a considerable time is required for building learners. For reduction of learning time, an improved method using multiclass classification is provided in this paper. By numerical evaluation, it was shown that the learners in the proposed method can be built in a considerably shorter time than the previous method when the same hyperparameters are used. But, from the point of view of solution time, a clear advantage could not be confirmed. Further investigation considering accuracy of the learners and appropriate settings of hyperparameters will be performed in a future work.

关键词： Data-driven job shop scheduling 0-1 mixed integer programming Multilayer neural network Solution time

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A robust optimization approach for steeling-continuous casting charge batch planning with uncertain slab weight

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JOURNAL OF PROCESS CONTROL 2024年 144卷

作者： Li, Congxin Sun, Liangliang Shenyang Jianzhu Univ Sch Mech Engn Shenyang 110168 Peoples R China Northeastern Univ Qinghuangdao Sch Control Engn Qinhuangdao 066004 Peoples R China

The volatility of slab weight in steelmaking-continuous casting (SCC) production, attributed to factors such as flexible order demand, is addressed in this paper. A robust optimization mathematical model for charge batch planning (CBP) with uncertain slab weight is established, and a collaborative optimization method using the surrogate Lagrangian relaxation (SLR) framework and improved objective feasibility pump (IOFP) is developed to solve the problem. In the SLR method, new step-size updating conditions are developed, eliminating the need for pre-estimating the optimal dual value. Additionally, only a subset of subproblems that satisfy the optimality conditions of the surrogate needs to be solved to overcome the low optimization efficiency resulting from oscillations in the feasible domain during internal searches in traditional Lagrangian relaxation (LR) methods. The IOFP method is employed to match the structure of the subproblem model of 0-1 mixed integer programming (MIP). During the search for integer solutions, a weighted objective function is added to the auxiliary model to improve the quality of solutions. Furthermore, it combines a variable neighborhood branching method to prevent the algorithm from entering into cycles. Finally, the effectiveness of the proposed model and the performance of the algorithm are validated through simulation experiments.

关键词： Charge batch planning Robust optimization Surrogate lagrangian relaxation Improved objective feasibility pump 0-1 mixed integer programming

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Passenger train scheduling on a single-track or partially double-track railway with stochastic information

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Engineering Optimization 2010年第11期42卷 1003-1022页

作者： Gao, Ziyou Li, Keping Yang, Lixing State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing People's Republic of China

This article investigates a scheduling problem for passenger trains on a single or partially double-track railway in which the total passengers' trip time with a penalty function is minimized. Owing to the uncertainty of the real traffic system, the number of passengers boarding (leaving) the train at each station is treated as a random variable. Three kinds of criteria are introduced to compute the total passengers' trip time, including the expected value criterion, the pessimistic value criterion and the optimistic value criterion. A 0-1 mixed integer programming model is constructed for the problem, and a branch-and-bound algorithm is also designed to solve the model, in which two strategies are introduced to resolve the conflicts on tracks. Finally, some numerical experiments are performed to show the performance of the model and the algorithm.

关键词： train schedule 0-1 mixed integer programming branch-and-bound algorithm random simulation

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