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A multi-criteria decision support methodology for real-time train scheduling

JOURNAL OF RAIL TRANSPORT PLANNING & MANAGEMENT 2015年第3期5卷 146-162页

作者： Sama, Marcella Meloni, Carlo D'Ariano, Andrea Corman, Francesco Univ Roma Tre Dipartimento Ingn Via Vasca Navale 79 I-00146 Rome Italy Politecn Bari Dipartimento Ingn Elettr & Informaz I-70125 Bari Italy CNR Ist Applicaz Calcolo Mauro Picone Sede Bari I-70126 Bari Italy Delft Univ Technol Transport Engn & Logist NL-2628 CD Delft Netherlands Katholieke Univ Leuven Ctr Ind Management B-3001 Leuven Belgium

This work addresses the real-time optimization of train scheduling decisions at a complex railway network during congested traffic situations. The problem of effectively managing train operations is particularly challenging, since it is necessary to incorporate the safety regulations into the optimization model and to consider key performance indicators. This paper deals with the development of a multi-criteria decision support methodology to help dispatchers in taking more informed decisions when dealing with real-time disturbances. Optimal train scheduling solutions are computed with high level precision in the modeling of the safety regulations and with consideration of state-of-the-art performance indicators. mixed-integer linear programming formulations are proposed and solved via a commercial solver. For each problem instance, an iterative method is proposed to establish an efficient-inefficient classification of the best solutions provided by the formulations via a well-established non-parametric benchmarking technique: data envelopment analysis. Based on this classification, inefficient formulations are improved by the generation of additional linear constraints. Computational experiments are performed for practical-size instances from a Dutch railway network with mixed traffic and several disturbances. The method converges after a limited number of iterations, and returns a set of efficient solutions and the relative formulations. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Railway traffic control Disturbance management Performance evaluation mixed-integer linear programming Data envelopment analysis

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A Computational Approach to Steady State Correspondence of Regular and Generalized Mass Action Systems

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BULLETIN OF MATHEMATICAL BIOLOGY 2015年第6期77卷 1065-1100页

作者： Johnston, Matthew D. Univ Wisconsin Dept Math Madison WI 53706 USA

It has been recently observed that the dynamical properties of mass action systems arising from many models of biochemical reaction networks can be characterized by considering the corresponding properties of a related generalized mass action system. The correspondence process known as network translation in particular has been shown to be useful in characterizing a system's steady states. In this paper, we further develop the theory of network translation with particular focus on a subclass of translations known as improper translations. For these translations, we derive conditions on the network topology of the translated network which are sufficient to guarantee the original and translated systems share the same steady states. We then present a mixed-integer linear programming algorithm capable of determining whether a mass action system can be corresponded to a generalized system through the process of network translation.

关键词： Chemical reaction network Mass action system Generalized network Network translation mixed-integer linear programming

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Virtual Network Embedding Under Uncertainty: Exact and Heuristic Approaches 11

Virtual Network Embedding Under Uncertainty: Exact and Heuri...

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11th International Conference on the Design of Reliable Communication Networks (DRCN)

作者： Coniglio, S. Koster, A. M. C. A. Tieves, M. Rhein Westfal TH Aachen Lehrstuhl Math 2 Aachen Germany

ISBN: (纸本)9781479977956

Given a physical substrate network and a collection of requests of virtual networks, the Virtual Network Embedding problem (VNE) calls for the embedding onto the physical substrate of a selection of virtual networks in such a way that the profit is maximized. The embedding corresponds to a virtual-to-physical mapping of nodes and links, subject to capacity constraints. Since, in practical scenarios, node and link demands are typically much smaller than the peak values specified in the virtual network requests, in this work we propose and investigate a robust optimization approach. This allows us to find solutions with a much larger profit which, at the same time, are guaranteed to be feasible with a high probability. To this end, we propose a robust mixed-integer linear programming (MILP) formulation for VNE, based on the well-known model of Gamma-robustness. To solve larger scale instances, for which the exact approach is computationally too demanding, we also propose a MILP-based two-phase heuristic which relies on Gamma-robustness.

关键词： virtual network embedding robust optimization mixed-integer linear programming Gamma-robustness

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Multi-Objective Distribution System Reconfiguration for Reliability Enhancement and Loss Reduction

Multi-Objective Distribution System Reconfiguration for Reli...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Paterakis, N. G. Santos, S. F. Catalao, J. P. S. Mazza, A. Chicco, G. Erdinc, O. Bakirtzis, A. G. INESC ID UBI Covilha Portugal IST Lisbon Portugal POLITO Turin Italy Yildiz Tech Univ Istanbul Turkey AUTh Thessaloniki Greece

ISBN: (纸本)9781467380409

This paper deals with the radial distribution system reconfiguration problem in a multi-objective scope, aiming to determine the optimal configuration by means of minimization of active power losses and several reliability indices. A novel way to calculate these indices under a mixed-integer linear programming (MILP) approach is provided. Afterwards, an efficient implementation of the e-constraint method using lexicographic optimization is employed to solve the multi-objective optimization problem, which is formulated as a MILP problem. After the Pareto Efficient solution set is generated, a multi-attribute decision making procedure is used, namely the technique for order preference by similarity to ideal solution (TOPSIS) method, so that a decision maker (DM) can express preferences over the solutions and facilitate the final selection.

关键词： Distribution system reconfiguration epsilonconstraint method loss minimization mixed-integer linear programming multi-objective optimization reliability

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An integrated sustainable partner selection approach with closed-loop supply chain network configuration 15

An integrated sustainable partner selection approach with cl...

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15th IFAC Symposium on Information Control Problems in Manufacturing

作者： Kafa, Nadine Hani, Yasmina El Mhamedi, Abederrahman Univ Paris 08 Equipe MGSI LISMMA 140 Rue La Nouvelle France F-93100 Montreuil France

Reverse logistics network design is a crucial issue in which it is important to take into account the selection of the most appropriate partner with sustainability concerns. This partner can be a supplier or a third-party reverse logistics provider (3PRLP). However, research works that consider reverse logistics (RL) network design, partner selection. and sustainability issues simultaneously are rather limited till now. This paper proposes an integrated sustainable approach for partner selection and closed-loop supply chain (CLSC) network configuration, particularly in the case of outsourcing reverse logistics process to third party provider. We propose a trade-off between sustainability criteria for both supplier and 3PRL provider selection. A multi-objective mixed-integer programming (MILP) model is also proposed to configure CLSC network and to select the best partners. The model minimizes the total cost of sourcing, and the total greenhouse gas emissions, while it maximizes the total value of reverse logistics, and the number of new job opportunities. A numerical example is also presented to illustrate the proposed approach. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Reverse logistics sustainable partner selection quantity allocation network configuration mixed-integer linear programming triple bottom line approach

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Efficient Deployment of Mobile Detectors for Security Applications

Efficient Deployment of Mobile Detectors for Security Applic...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Baumann, Philipp Cooper, Reynold J. Hochbaum, Dorit S. Patel, Nidhi Shalia, Kunal Univ Calif Berkeley Dept Ind Engn & Operat Res Berkeley CA 94720 USA Lawrence Berkeley Natl Lab Berkeley CA USA

ISBN: (纸本)9781467380669

We present a real-world problem that arises in security threat detection applications. The problem consists of deploying mobile detectors on moving units that follow predefined routes. Examples of such units are buses, coaches, and trolleys. Due to a limited budget not all available units can be equipped with a detector. The goal is to equip a subset of units such that the utility of the resulting coverage is maximized. Existing methods for detector deployment are designed to place detectors in fixed locations and are therefore not applicable to the problem considered here. We formulate the planning problem as a binary linear program and present a coverage heuristic for generating effective deployments in short CPU time. The heuristic has theoretical performance guarantees for important special cases of the problem. The effectiveness of the coverage heuristic is demonstrated in a computational analysis based on 28 instances that we derived from real-world data.

关键词： Threat detection mobile detector deployment problem mixed-integer linear programming coverage heuristic

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A Real-Time Decision Support Tool for Disaster Response: A Mathematical programming Approach 4

A Real-Time Decision Support Tool for Disaster Response: A M...

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IEEE International Congress on Big Data

作者： Kuo, Yong-Hong Leung, Janny M. Y. Meng, Helen M. Tsoi, Kelvin K. F. Chinese Univ Hong Kong Stanley Ho Big Data Decis Analyt Res Ctr Shatin Hong Kong Peoples R China Chinese Univ Hong Kong Dept Syst Engn & Engn Management Shatin Hong Kong Peoples R China Chinese Univ Hong Kong Sch Publ Hlth & Primary Care Shatin Hong Kong Peoples R China

ISBN: (纸本)9781467372787

Disasters are sudden and calamitous events that can cause severe and pervasive negative impacts on society and huge human losses. Governments and humanitarian organizations have been putting tremendous efforts to avoid and reduce the negative consequences due to disasters. In recent years, information technology and big data have played an important role in disaster management. While there has been much work on disaster information extraction and dissemination, real-time optimization for decision support for disaster response is rarely addressed in big data research. In this paper, we propose a mathematical programming approach, with real-time disaster-related information, to optimize the post-disaster decisions for emergency supplies delivery. This decision support tool can provide rapid and effective solutions, which are essential for disaster response.

关键词： disaster response real-time disaster data humanitarian logistics emergency supplies mathematical modeling optimization mixed-integer linear programming

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Index Tracking Using Data-Mining Techniques and mixed-Binary linear programming

Index Tracking Using Data-Mining Techniques and Mixed-Binary...

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IEEE International Conference on Industrial Engineering and Engineering Management IEEM

作者： Strub, Oliver Baumann, Philipp Univ Bern Dept Business Adm Bern Switzerland Univ Calif Berkeley Dept Ind Engn & Operat Res Berkeley CA USA

ISBN: (纸本)9781467380669

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

关键词： Cross validation data mining index tracking mixed-integer linear programming principal component analysis

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Improving Fairness in Staff Assignment: An Approach for Lexicographic Goal programming

Improving Fairness in Staff Assignment: An Approach for Lexi...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Rihm, Tom Baumann, Philipp Univ Bern Dept Business Adm Bern Switzerland Univ Calif Berkeley Dept Ind Engn & Operat Res Berkeley CA USA

ISBN: (纸本)9781467380669

In many staff-assignment problems, a large variety of requirements has to be considered when assigning employees to work shifts. As the importance of the requirements is often described in a hierarchical manner, lexicographic goal programming has been used to minimize the number of requirement violations. The resulting schedules are in general of high quality with respect to requirement violations but may lack acceptance by employees because of an unfair distribution of the violations. We introduce a novel approach for lexicographic goal programming that allows to improve an existing schedule in terms of fairness without deteriorating its quality with regard to requirement violations. The effectiveness of the proposed approach is demonstrated for a test set derived from real-world data.

关键词： Staff Assignment Fairness Multi-Objective programming mixed-integer linear programming

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Offering Strategies of Wind Power Producers in a Day-Ahead Electricity Market 6

Offering Strategies of Wind Power Producers in a Day-Ahead E...

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6th IFIPWG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS)

作者： Laia, R. Pousinho, H. M. I. Melicio, R. Mendes, V. M. F. Collares-Pereira, M. Univ Evora Evora Portugal Univ Lisbon Inst Super Tecn IDMEC LAETA P-1699 Lisbon Portugal Inst Super Engn Lisboa Lisbon Portugal

ISBN: (纸本)9783319167664;9783319167657

This paper presents a stochastic optimization-based approach applied to offer strategies of a wind power producer in a day-ahead electricity market. Further from facing the uncertainty on the wind power the market forces wind power producers to face the uncertainty of the market-clearing electricity price. Also, the producer faces penalties in case of being unable to fulfill the offer. An efficient mixed-integer linear program is presented to develop the offering strategies, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

关键词： mixed-integer linear programming Stochastic optimization Wind power Offering strategies

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