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Spatial Power Network Expansion Planning Considering Generation Expansion

IEEE TRANSACTIONS ON POWER SYSTEMS 2015年第4期30卷 1815-1824页

作者： Shu, Jun Wu, Lei Zhang, Lizi Han, Bing North China Elect Power Univ Dept Elect Engn Beijing 102206 Peoples R China Clarkson Univ Elect & Comp Engn Dept Potsdam NY 13699 USA China Three Gorges Corp Dept Mkt Beijing Peoples R China

This paper introduces an efficient approach on static spatial power network expansion planning integrated with generation expansion, while considering complicated environments based on the raster map in geographic information systems (GIS). Candidate plants could be built on any cell in the map, which means that terminals of candidate lines connected to candidate plants are not fixed. This is a remarkable difference from the literature in which the terminals of candidate lines are fixed. The objective is to minimize the total system cost, subject to prevailing investment and operation constraints. The model is formulated as a mixed-integer linear programming (MILP) problem via integer algebra techniques. A two-step approach is proposed to address the computational complexity. The first step searches optimal electric line routes via dynamic programming, while the second step solves a simplified MILP problem for obtaining final optimal generation and transmission planning strategies based on optimal line routes derived from the first step. In most cases, the proposed two-step approach would derive the same global optimal solutions as those by solving the original formulation directly. Thus, the proposed two-step approach can significantly improve the computational efficiency while maintaining the solution optimality. Numerical examples demonstrate the effectiveness of the proposed approach.

关键词： Dynamic programming generation expansion geographic information systems mixed-integer linear programming power network planning routing

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A quantitative assessment on the placement practices of gas detectors in the process industries

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JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES 2015年 35卷 339-351页

作者： Benavides-Serrano, A. J. Mannan, M. S. Laird, C. D. Texas A&M Univ Dept Chem Engn Artie McFerrin Dept Chem Engn College Stn TX 77843 USA Texas A&M Univ Mary Kay OConnor Proc Safety Ctr Artie McFerrin Dept Chem Engn College Stn TX 77843 USA Purdue Univ Sch Chem Engn W Lafayette IN 47907 USA

Gas detection is an important safety system with interfaces to several other safety safeguards. However, the generality of the regulations, standards and recommended practices in conjunction with the inherent challenges of the gas detector placement problem, has resulted in a widespread use of prescriptive and qualitative detector placement strategies. In order to take advantage of the quantitative information provided by dispersion simulations, a stochastic programming formulation (SP-UV) was previously proposed, developed and validated by the authors. This formulation identifies the gas detector layout that minimizes the expected value of an overall damage coefficient (i.e., the minimization of a risk metric) given a set of dispersion scenarios. Results demonstrated the potential and suitability of numerical optimization to solve the gas detector placement problem while rigorously considering its inherent uncertainties. In this work, four existing approaches for gas detector placement were implemented and compared with the previously proposed quantitative optimization-based approach using three different performance metrics in accordance to the objectives of gas detection systems. Results provide evidence on the effectiveness of the use of dispersion simulations, and mathematical programming, to supplement the gas detector placement problem. (c) 2014 Published by Elsevier Ltd.

关键词： Gas detection Process safety Detector placement Stochastic programming mixed-integer linear programming Unavailability Backup coverage Voting

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A decomposition-based heuristic for the multiple-product inventory-routing problem

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COMPUTERS & OPERATIONS RESEARCH 2015年第Mar.期55卷 153-166页

作者： Cordeau, Jean-Francois Lagana, Demetrio Musmanno, Roberto Vocaturo, Francesca HEC Montreal Montreal PQ H3T 2A7 Canada Univ Calabria Dept Mech Energy & Management Engn I-87036 Arcavacata Di Rende CS Italy Univ Calabria Dept Econ Stat & Finance I-87036 Arcavacata Di Rende Italy

The inventory-routing problem is an integrated logistics planning problem arising in situations where customers transfer the responsibility for inventory replenishment to the vendor. The vendor must then decide when to visit each customer, how much to deliver and how to sequence customers in vehicle routes. In this paper, we focus on the case where several different products have to be delivered by a fleet of vehicles over a finite and discrete planning horizon. We present a three-phase heuristic based on a decomposition of the decision process of the vendor. In the first phase, replenishment plans are determined by using a Lagrangian-based method. These plans do not specify delivery sequences for the vehicles. The sequencing of the planned deliveries is performed in the second phase in which a simple procedure is employed to construct vehicle routes. The third phase incorporates planning and routing decisions into a mixed-integer linear programming model aimed at finding a good solution to the integrated problem. Computational experiments show that our heuristic is effective on instances with up to 50 customers and 5 products. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Inventory-routing Heuristic mixed-integer linear programming Lagrangian relaxation

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A supply chain design approach considering environmentally sensitive customers: the case of a German manufacturing SME

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2015年第21期53卷 6534-6550页

作者： Altmann, Michael Univ Wurzburg Chair Business Management & Ind Management D-97070 Wurzburg Germany

Sustainable business development is one of the main topics of research and management in recent years. Since the environmental pillar is a part of the sustainability concept, companies are forced to (re-)design their supply chain according to environmental issues. Both government and other stakeholders, e.g. non-governmental organisations and customers, pay a lot of attention on a company's environmental performance. Hence there is a risk of losing reputation if a company does not comply with environmental norms. We focus on the impact of customers' requirements regarding the environmental performance of a product on strategic supply chain design decisions of the manufacturer of the product. Thus, we consider the case of a German manufacturing company and present a mixed-integer linear programming supply chain design model with a demand function that is influenced by sustainability requirements. The company is assumed to be able to improve the environmental performance of the products sold and affect the customer demand positively by designing an environmentally conscious supply chain.

关键词： mixed-integer linear programming sustainable manufacturing supply chain design case study

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AM-Band: An Asymmetrical Multi-Band model for arterial traffic signal coordination

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2015年第PartC期58卷 515-531页

作者： Zhang, Chao Xie, Yuanchang Gartner, Nathan H. Stamatiadis, Chronis Arsava, Tugba MIT Dept Civil & Environm Engn Cambridge MA 02139 USA Univ Massachusetts Dept Civil & Environm Engn Lowell MA 01854 USA

MAXBAND and MULTIBAND are two well-recognized methods for arterial signal control. In this paper, an Asymmetrical Multi-BAND (AM-BAND) model is developed by relaxing the symmetrical progression band requirement in MULTIBAND. Such a relaxation allows the AM-BAND model to better utilize the available green times in each direction and to provide additional opportunities for vehicular progression. Similar to MULTIBAND, the proposed AM-BAND model is formulated as a mixed-integer linear program. However, in AM-BAND the green bands in each directional section of the arterials do not have to be symmetrical with respect to the progression line. The performance of the AM-BAND model is evaluated for two arterial network data using the AIMSUN microscopic traffic simulation tool. The optimal signal coordination plans are computed by the IBM CPLEX Optimization Studio and compared with signal timing plans generated by AM-BAND, MULTIBAND, and MAXBAND. Simulation results indicate that the traffic signal coordination plans generated by AM-BAND can provide significant benefits compared to those generated by MAXBAND and MULTIBAND. Published by Elsevier Ltd.

关键词： Traffic signal coordination MAXBAND MULTIBAND mixed-integer linear programming Traffic simulation

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RECIFE-MILP: An Effective MILP-Based Heuristic for the Real-Time Railway Traffic Management Problem

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2015年第5期16卷 2609-2619页

作者： Pellegrini, Paola Marliere, Gregory Pesenti, Raffaele Rodriguez, Joaquin Univ Lille Nord France F-59000 Lille France LEOST COSYS IFSTTAR F-59650 Villeneuve Dascq France ESTAS COSYS IFSTTAR F-59650 Villeneuve Dascq France Ca Foscari Univ I-30121 Venice Italy

The real-time railway traffic management problem consists of selecting appropriate train routes and schedules for minimizing the propagation of delay in case of traffic perturbation. In this paper, we tackle this problem by introducing RECIFE-MILP, a heuristic algorithm based on a mixed-integer linear programming model. RECIFE-MILP uses a model that extends one we previously proposed by including additional elements characterizing railway reality. In addition, it implements performance boosting methods selected among several ones through an algorithm configuration tool. We present a thorough experimental analysis that shows that the performances of RECIFE-MILP are better than the ones of the currently implemented traffic management strategy. RECIFE-MILP often finds the optimal solution to instances within the short computation time available in real-time applications. Moreover, RECIFE-MILP is robust to its configuration if an appropriate selection of the combination of boosting methods is performed.

关键词： Real-time railway traffic management problem mixed-integer linear programming algorithm configuration performance boosting

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Dynamic design and re-design of multi-echelon, multi-product logistics networks with outsourcing opportunities: A computational study

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COMPUTERS & INDUSTRIAL ENGINEERING 2015年 90卷 118-131页

作者： Cortinhal, M. J. Lopes, M. J. Melo, M. T. Inst Univ Lisboa ISCTE IUL P-1649026 Lisbon Portugal Univ Lisbon CMAE CIO P-1749016 Lisbon Portugal Saarland Univ Appl Sci Sch Business D-66123 Saarbrucken Germany

We address the problem of designing/redesigning a multi-echelon logistics network over multiple periods. Strategic decisions comprise opening new facilities and selecting their capacities from a set of available discrete sizes. Capacity expansion may occur more than once over the time horizon both at new locations and at existing facilities. In addition, logistics decisions involving supplier selection, procurement, production, and distribution of multiple products are to be made. The latter also involve the choice of transportation modes with limited capacities. Finally, a strategic choice between in-house manufacturing and a mixed approach with product outsourcing is to be taken. We propose a mixed-integer linear programming model and develop additional inequalities to enhance the original formulation. To gain insight into the complexity of the problem at hand, an extensive computational study is performed with randomly generated instances that are solved with standard mathematical optimization software. Useful managerial insights are derived from varying several parameters and analyzing the impact of different business strategies on various segments of the logistics network. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Logistics network design/re-design Multiple periods Transportation mode selection Product outsourcing mixed-integer linear programming

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Formulations and algorithms for the multiple depot, fuel-constrained, multiple vehicle routing problem

Formulations and algorithms for the multiple depot, fuel-con...

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American Control Conference

作者： Kaarthik Sundar Saravanan Venkatachalam Sivakumar Rathinam Dept. of Mechanical Engg. Texas A&M University College Station 77843 USA Dept. of Industrial and Systems Engg. Wayne State University Detroit MI 48202 USA

ISBN: (纸本)9781467386838

We consider a multiple depot, multiple vehicle routing problem with fuel constraints. We are given a set of targets, a set of depots and a set of homogeneous vehicles, one for each depot. The depots are also allowed to act as refueling stations. The vehicles are allowed to refuel at any depot, and our objective is to determine a route for each vehicle with a minimum total cost such that each target is visited at least once by some vehicle, and the vehicles never run out fuel as it traverses its route. We refer to this problem as the Multiple Depot, Fuel-Constrained, Multiple Vehicle Routing Problem (FCMVRP). This paper presents four new mixed integer linear programming formulations to compute an optimal solution for the problem. Extensive computational results for a large set of instances are also presented.

关键词： unmanned vehicle routing fuel constraints green vehicle routing electric vehicles mixed-integer linear programming WAREHOUSE vehicle Electric vehicles mixed integer linear programming Vehicle routing Total Costs Refuelling

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A new algorithm to find all alternate optimal flux distributions of a metabolic network

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COMPUTERS & CHEMICAL ENGINEERING 2015年 73卷 64-69页

作者： Motamedian, Ehsan Tarbiat Modares Univ Dept Chem Engn Biotechnol Grp Tehran Iran

Finding all optimal solutions for a metabolic model is the challenge of metabolic modeling, but there is no practical algorithm for large scale models. A two-phase algorithm is proposed here to systematically identify all optimal solutions. In phase 1, the model is reduced using the FVA approach;in phase 2, all optimal solutions are searched by the addition of a binary variable to convert the model to an MILP problem. The proposed approach proved itself to be a more tractable method for large scale metabolic models when compared with the previously proposed algorithm. The algorithm was implemented on a metabolic model of Escherichia coli (iJR904) to find all optimal flux distributions. The model was reduced from 1076 to 80 fluxes and from 998 to 54 equations and the MILP problem was solved, resulting in 30,744 various flux distributions. For the first time, this number of optimal solutions has been reported. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Flux balance analysis Metabolic network Multiple optimal solutions Flux variability mixed-integer linear programming

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Multi-product valid inequalities for the discrete lot-sizing and scheduling problem

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COMPUTERS & OPERATIONS RESEARCH 2015年 54卷 12-20页

作者： Gicquel, C. Minoux, M. Univ Paris 11 Rech Informat Lab F-91405 Orsay France Univ Paris 06 Lab Informat Paris 6 F-75005 Paris France

We consider a problem arising in the context of industrial production planning, namely the multi-product discrete lot-sizing and scheduling problem with sequence-dependent changeover costs. We aim at developing an exact solution approach based on a Cut & Branch procedure for this combinatorial optimization problem. To achieve this, we propose a new family of multi-product valid inequalities which corresponds to taking into account the conflicts between different products simultaneously requiring production on the resource. We then present both an exact and a heuristic separation algorithm which form the basis of a cutting-plane generation algorithm. We finally discuss computational results which confirm the practical usefulness of the proposed inequalities at strengthening the MILP formulation and at reducing the overall computation time. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Production planning Discrete lot-sizing problem mixed-integer linear programming Valid inequalities

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