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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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Global optimization method for network design problem with stochastic user equilibrium

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2015年 72卷 20-39页

作者： Liu, Haoxiang Wang, David Z. W. Nanyang Technol Univ Sch Civil & Environm Engn Singapore 639798 Singapore

In this paper, we consider the continuous road network design problem with stochastic user equilibrium constraint that aims to optimize the network performance via road capacity expansion. The network flow pattern is subject to stochastic user equilibrium, specifically, the logit route choice model. The resulting formulation, a nonlinear nonconvex programming problem, is firstly transformed into a nonlinear program with only logarithmic functions as nonlinear terms, for which a tight linear programming relaxation is derived by using an outer-approximation technique. The linear programming relaxation is then embedded within a global optimization solution algorithm based on range reduction technique, and the proposed approach is proved to converge to a global optimum. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Network design problem Stochastic user equilibrium mixed-integer linear programming Global optimization Range reduction technique

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Clustering Algorithm of Hierarchical Structures in Large-Scale Wireless Sensor and Actuator Networks

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JOURNAL OF COMMUNICATIONS AND NETWORKS 2015年第5期17卷 473-481页

作者： Pham Tran Anh Quang Kim, Dong-Seong IRISA INRIA Rennes Res Ctr Rennes France Kumoh Natl Inst Technol Sch Elect Engn Seoul South Korea

In this study, we propose a clustering algorithm to enhance the performance of wireless sensor and actuator networks (WSANs). In each cluster, a multi-level hierarchical structure can be applied to reduce energy consumption. In addition to the cluster head, some nodes can be selected as intermediate nodes (INs). Each IN manages a subcluster that includes its neighbors. INs aggregate data from members in its subcluster, then send them to the cluster head. The selection of intermediate nodes aiming to optimize energy consumption can be considered high computational complexity mixed-integer linear programming. Therefore, a heuristic lowest energy path searching algorithm is proposed to reduce computational time. Moreover, a channel assignment scheme for sub-clusters is proposed to minimize interference between neighboring subclusters, thereby increasing aggregated throughput. Simulation results confirm that the proposed scheme can prolong network lifetime in WSANs.

关键词： Clustering algorithm hierarchical structure large-scale mixed-integer linear programming wireless sensor network

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A space-discretized mixed-integer linear model for air-conflict resolution with speed and heading maneuvers

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COMPUTERS & OPERATIONS RESEARCH 2015年 58卷 75-86页

作者： Omer, Jeremy Ecole Polytech Montreal PQ H3T 1J4 Canada HEC Montreal Grp Res Decis Anal Montreal PQ H3T 2A7 Canada

Air-conflict resolution is a bottleneck of air traffic management that will soon require powerful decision-aid systems to avoid the proliferation of delays. Since reactivity is critical for this application, we develop a mixed-integer linear model based on space discretization so that complex situations can be solved in near real-time. The discretization allows us to model the problem with finite and potentially small sets of variables and constraints by focusing on important points of the planned trajectories, including the points where trajectories intersect. A major goal of this work is to use space discretization while allowing velocity and heading maneuvers. Realistic trajectories are also ensured by considering speed vectors that are continuous with respect to time, and limits on the velocity, acceleration, and yaw rate. A classical indicator of economic efficiency is then optimized by minimizing a weighted sum of fuel consumption and delay. The experimental tests confirm that the model can solve complex situations within a few seconds without incurring more than a few kilograms of extra fuel consumption per aircraft. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Conflict resolution Space discretization Air traffic control mixed-integer linear programming

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Optimal scheduling of distributed battery storage for enhancing the security and the economics of electric power systems with emission constraints

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ELECTRIC POWER SYSTEMS RESEARCH 2015年 124卷 152-159页

作者： Haddadian, G. Khalili, N. Khodayar, M. Shahidehpour, M. IIT Stuart Sch Business Chicago IL 60616 USA So Methodist Univ LYLE Sch Engn Dallas TX 75205 USA IIT Elect & Comp Engn Dept Chicago IL 60616 USA King Abdulaziz Univ Elect & Comp Engn Dept Jeddah 21413 Saudi Arabia

In this paper, the sustainable day-ahead scheduling of electric power systems with the integration of distributed energy storage devices is investigated. The main objective is to minimize the hourly power system operation cost with a cleaner, socially responsible, and sustainable generation of electricity. Emission constraints are enforced to reduce the carbon footprint of conventional thermal generating units. The stationary electric vehicles (EV) are considered as an example of distributed storage and vehicle to grid (V2G) technology is considered to demonstrate the bilateral role of EV as supplier and consumer of energy. Battery storage can ease the impact of variability of renewable energy sources on power system operations and reduce the impact of thermal generation emission at peak hours. We model the day-ahead scheduling of electric power systems as a mixed-integer linear programing (MILP) problem for solving the hourly security-constraint unit commitment (SCUC). In order to expedite the real-time solution for large-scale power systems, we consider a two-stage model of the hourly SCUC by applying the Benders decomposition (BD). The Benders decomposition would separate the hourly generation unit commitment (UC) in the master problem from the power network security check in subproblem. The subproblem would check dc network security constraints for the given UC solution to determine whether a converged and secure dc power flow can be obtained. If any power network violations arise, corresponding Benders cuts are formed and added to the master problem for solving the next iteration of UC. The iterative process will continue until the network violations are eliminated and a converged hourly solution is found for scheduling the power generating units. Numerical simulations are presented to illustrate the effectiveness of the proposed MILP approach and its potentials as an optimization tool for sustainable operations of electric power grids. (C) 2015 Elsevier B.V. A

关键词： Sustainable electricity generation V2G Security-constrained unit commitment mixed-integer linear programming Smart grid Electric vehicles

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A MILP-Based Distribution Optimal Power Flow Model for Microgrid Operation

A MILP-Based Distribution Optimal Power Flow Model for Micro...

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IEEE Power and Energy Society General Meeting

作者： Guodong Liu Michael Starke Xiaohu Zhang Kevin Tomsovic Power & Energy Systems Group Oak Ridge National Laboratory Dept. of Electrical Engineering and Computer Science The University of Tennessee

ISBN: (纸本)9781509041695

This paper proposes a distribution optimal power flow (D-OPF) model for the operation of microgrids. The proposed model minimizes not only the operating cost, including fuel cost, purchasing cost and demand charge, but also several performance indices, including voltage deviation, network power loss and power factor. It co-optimizes the real and reactive power form distributed generators (DGs) and batteries considering their capacity and power factor limits. The D-OPF is formulated as a mixed-integer linear programming (MILP). Numerical simulation results show the effectiveness of the proposed model.

关键词： Distribution optimal power flow Microgrids Distributed generators Multiobjective optimization mixed-integer linear programming MICRO-GRID Reactive power optimal load flow mixed integer linear programming performance indicators Surgery Batteries voltage error

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Generation Ramping Valuation in Day-Ahead Electricity Markets

Generation Ramping Valuation in Day-Ahead Electricity Market...

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Hawaii International Conference on System Sciences

作者： Masood Parvania Anna Scaglione Department of Electrical and Computer Engineering University of Utah School of Electrical Computer and Energy Engineering Arizona State University

ISBN: (纸本)9781509019816

In this paper, we first introduce a variational formulation of the Unit Commitment (UC) problem, in which generation and ramping trajectories of the generating units are continuous time signals and the generating units cost depends on the three signals: the binary commitment status of the units as well as their continuous-time generation and ramping trajectories. We assume such bids are piecewise strictly convex time-varying linear functions of these three variables. Based on this problem derive a tractable approximation by constraining the commitment trajectories to switch in a discrete and finite set of points and representing the trajectories in the function space of piece-wise polynomial functions within the intervals, whose discrete coefficients are then the UC problem decision variables. Our judicious choice of the signal space allows us to represent cost and constraints as linear functions of such coefficients;thus, our UC models preserves the MILP formulation of the UC problem. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total day-ahead and real-time operation cost, and the number of ramping scarcity events in the real-time operations.

关键词： Unit commitment Generation trajectory Ramping trajectory Ramping cost Continuous-time function space mixed-integer linear programming

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