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Optimal traffic calming: A mixed-integer bi-level programming model for locating sidewalks and crosswalks in a multimodal transportation network to maximize pedestrians' safety and network usability

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2016年 91卷 33-50页

作者： Rashidi, Eghbal Parsafard, Mohsen Medal, Hugh Li, Xiaopeng Mississippi State Univ Dept Ind & Syst Engn Mississippi State MS 39762 USA Univ S Florida Dept Civil & Environm Engn Tampa FL 33620 USA

We study the effect that installing sidewalks and crosswalks, as traffic calming facilities, has on the safety and usability of a transportation network with automobile, public transit and walking as modes of transportation. A mathematical programming model is proposed for this problem whose objective is to minimize the safety hazard for pedestrians and the total transportation cost of the network. We utilize a customized greedy heuristic and a simulated annealing algorithm for solving the problem. The computational results indicate that installing sidewalks and crosswalks at proper locations can reduce the overall transportation cost and improve pedestrians' safety. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Multimodal transportation network mixed-integer nonlinear programming Network design Pedestrians' safety Traffic calming User equilibrium

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Cutting Plane Algorithm for Convex Generalized Disjunctive Programs

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INFORMS JOURNAL ON COMPUTING 2016年第2期28卷 209-222页

作者： Trespalacios, Francisco Grossmann, Ignacio E. Carnegie Mellon Univ Pittsburgh PA 15213 USA

In this work, we propose a cutting plane algorithm to improve optimization models that are originally formulated as convex generalized disjunctive programs. Generalized disjunctive programs are traditionally reformulated as mixed-integer nonlinear programming (MINLP) problems using either the big M (BM) or the hull reformulation (HR). The former yields a smaller MILP/MINLP problem, whereas the latter yields a tighter one. The HR can be further strengthened by using the concept of basic step from disjunctive programming. The proposed algorithm uses the strengthened formulation to derive cuts for the big-M formulation, generating a stronger formulation with small growth in problem size. We test the algorithm with several instances. The results show that the algorithm improves generalized disjunctive programming convex models, in the sense of providing formulations with stronger continuous relaxations than the BM formulation, with few additional constraints. In general, the algorithm also leads to a reduction in the solution time of the problems.

关键词： generalized disjunctive programming mixed-integer nonlinear programming

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Multi-objective optimization of biomass to biomethane system

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Green Energy & Environment 2016年第2期1卷 156-165页

作者： Nana Yan Baozeng Ren Bin Wu Di Bao Xiangping Zhang Jingheng Wang State Key Laboratory of Laboratory of Green Process and Engineering Institute of Process Engineering Chinese Academy of Sciences School of Chemical Engineering and Energy Zhengzhou University

The superstructure optimization of biomass to biomethane system through digestion is conducted in this work. The system encompasses biofeedstock collection and transportation, anaerobic digestion, biogas upgrading, and digestate recycling. We propose a multicriteria mixed integer nonlinear programming(MINLP) model that seeks to minimize the energy consumption and maximize the green degree and the biomethane production constrained by technology selection, mass balance, energy balance, and environmental impact. A multi-objective MINLP model is proposed and solved with a fast nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). The resulting Pareto-optimal surface reveals the trade-off among the conflicting objectives. The optimal results indicate quantitatively that higher green degree and biomethane production objectives can be obtained at the expense of destroying the performance of the energy consumption objective.

关键词： Multiobjective optimization Biomass to biomethane system Green degree mixed-integer nonlinear programming

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Informing pediatric vaccine procurement policy via the pediatric formulary design, pricing, and production problem

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IIE TRANSACTIONS 2016年第12期48卷 1112-1126页

作者： Lunday, Brian Robbins, Matthew J. Air Force Inst Technol Dept Operat Sci Wright Patterson AFB OH USA

This research improves upon the monopsonist vaccine formulary design problem in the literature by incorporating several modeling enhancements and applying different methodologies to efficiently obtain solutions and derive insights. Our multi-objective formulation seeks to minimize the overall price to immunize a cohort of children, maximize the net profit shared among pediatric vaccine manufacturers, and minimize the average number of injections per child among the prescribed formularies. Accounting for Centers for Disease Control and Prevention (CDC) guidelines, we restrict vaccines utilized against a given disease within a given formulary to those produced by a single manufacturer. We also account for a circumstance in which one manufacturer's vaccine has a greater relative efficacy. For the resulting nonconvex mixed-integer nonlinear program, we bound the second and third objectives using optimal formulary designs for current public sector prices and utilize the E -constraint method to solve an instance representative of contemporary immunization schedule requirements. Augmenting our formulation with symmetry reduction constraints to reduce the required computational effort, we identify a set of non-inferior solutions. Of practical interest to the CDC, our model enables the design of a pricing and purchasing policy, creating a sustainable and stable capital investment environment for the provision of pediatric vaccines.

关键词： Multi-objective optimization mixed-integer nonlinear programming vaccine economics

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Superstructure Optimization of Integrated Fast Pyrolysis-Gasification for Production of Liquid Fuels and Propylene

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AICHE JOURNAL 2016年第9期62卷 3155-3176页

作者： Yuan, Zhihong Eden, Mario R. Auburn Univ Dept Chem Engn Auburn AL 36849 USA

Motivated by the apparent advantages of fast pyrolysis and gasification, a novel integrated biorefinery plant is systematically synthesized for coproducing premium quality liquid fuels and propylene. The required heat and fluidization promotion of the fast pyrolyzer are provided by hot syngas from the gasifier. Light gas and syngas from the fast pyrolyzer are finally converted to hydrocarbons via Fischer-Tropsch synthesis. Multiple syngas production technologies, hydrocarbon production and downstream upgrading routes are incorporated within a superstructure optimization based process synthesis framework. This is the first article to investigate the benefits associated with the introduction of conventional catalytic cracking and dewaxing from a systems engineering perspective. Surrogate models describing the gasifiers and rigorous equations for Fischer-Tropsch effluents validated by our experimental collaborator are introduced. Through investigation of five scenarios the primary parameters affecting overall economic performance are identified through ranking of the relevant candidates. Comparisons of the hybrid conversion route and stand-alone routes are made. VC (C) 2016 American Institute of Chemical Engineers

关键词： gasification fast pyrolysis mixed-integer nonlinear programming superstructure premium quality transportation fuels propylene

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Towards an objective feasibility pump for convex MINLPs

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2016年第3期63卷 737-753页

作者： Sharma, Shaurya Knudsen, Brage Rugstad Grimstad, Bjarne Ellipt Labs AS Sandakerveien 24C N-0473 Oslo Norway Norwegian Univ Sci & Technol Dept Engn Cybernet N-7491 Trondheim Norway

This paper describes a heuristic algorithm for finding good feasible solutions of convex mixed-integer nonlinear programs (MINLPs). The algorithm we propose is a modification of the feasibility pump heuristic, in which we aim at balancing the two goals of quickly obtaining a feasible solution and preserving quality of the solution with respect to the original objective. The effectiveness and merits of the proposed algorithm are assessed by evaluation of extensive computational results from a set of 146 convex MINLP test problems. We also show how a set of user-defined parameters may be selected to strike a balance between low computation time and high solution quality.

关键词： mixed-integer programming heuristics Feasibility pump mixed-integer nonlinear programming Primal heuristics

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Reactor network synthesis with guaranteed robust stability

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COMPUTERS & CHEMICAL ENGINEERING 2016年 86卷 75-89页

作者： Zhao, Xiao Marquardt, Wolfgang Rhein Westfal TH Aachen Proc Syst Engn Aachener Verfahrenstech Templergraben 56 D-52056 Aachen Germany Forschungszentrum Julich D-52425 Julich Germany

This paper proposes a systematic approach to design reactor networks with guaranteed robust stability. The approach is based on the superstructure approach for reactor network synthesis. A structured dynamic model for reactor network modeling is formulated and embedded in a MINLP with robust eigenvalue constraints. Design parameters, structural alternatives and parametric uncertainty are considered simultaneously as design degrees of freedom. Structural alternatives result from decisions on the existence of reactors and flow connections in the superstructure. Parametric uncertainty may either result from model uncertainties such as reaction kinetic constants or heat transfer coefficients, or from process uncertainties including slow disturbances in load or quality of raw materials. A tailored two-step solution strategy is proposed to tackle the robust mixed -integer optimization problem. A case study with five continuous stirred -tank reactors (CSTR) and five plug flow reactors (PFR) is presented for illustration. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Reactor network synthesis Robust stability mixed-integer nonlinear programming Normal vector approach Superstructure approach Robust optimization

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An adaptive discretization MINLP algorithm for optimal synthesis of decentralized energy supply systems

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COMPUTERS & CHEMICAL ENGINEERING 2016年 95卷 38-48页

作者： Goderbauer, Sebastian Bahl, Bjoern Voll, Philip Luebbecke, Marco E. Bardow, Andre Koster, Arie M. C. A. Rhein Westfal TH Aachen Lehrstuhl Math 2 D-52056 Aachen Germany Rhein Westfal TH Aachen Operat Res D-52072 Aachen Germany Rhein Westfal TH Aachen Chair Tech Thermodynam D-52056 Aachen Germany

Decentralized energy supply systems (DESS) are highly integrated and complex systems designed to meet time-varying energy demands, e.g., heating, cooling, and electricity. The synthesis problem of DESS addresses combining various types of energy conversion units, choosing their sizing and operations to maximize an objective function, e.g., the net present value. In practice, investment costs and part-load performances are nonlinear. Thus, this optimization problem can be modeled as a nonconvex mixed-integer nonlinear programming (MINLP) problem. We present an adaptive discretization algorithm to solve such synthesis problems containing an iterative interaction between mixed-integer linear programs (MIPs) and nonlinear programs (NLPs). The proposed algorithm outperforms state-of-the-art MINLP solvers as well as linearization approaches with regard to solution quality and computation times on a test set obtained from real industrial data, which we made available online. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： mixed-integer nonlinear programming Decentralized energy supply system Synthesis Structural optimization Adaptive discretization

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An overview of exact algorithms for the Euclidean Steiner tree problem in n-space

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2016年第5期23卷 861-874页

作者： Fampa, Marcia Lee, Jon Maculan, Nelson Univ Fed Rio de Janeiro Inst Matemat Dept Ciencia Comp Rio De Janeiro RJ Brazil Univ Fed Rio de Janeiro COPPE PESC Rio De Janeiro RJ Brazil Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA

The Euclidean Steiner tree problem (ESTP) in R-n is to find a shortest network interconnecting p given points in n-dimensional Euclidean space. The problem was first described in the plane and an algorithm with very good practical efficiency has been proposed to solve this particular case. The generalization for higher dimensions was proposed in the 19th century, however the numerical solution of the problem remains very challenging when n >= 3. We give an overview of the exact algorithms presented in the literature for the ESTP when n >= 3 and discuss their common and distinguished features, their advantages and drawbacks, and some possible directions for improvement toward the numerical solution of large instances of the problem.

关键词： Euclidean Steiner tree problem n-dimensional Euclidean space exact algorithm mixed-integer nonlinear programming global optimization

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Global optimization of multiphase flow networks using spline surrogate models

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COMPUTERS & CHEMICAL ENGINEERING 2016年 84卷 237-254页

作者： Grimstad, Bjarne Foss, Bjarne Heddle, Richard Woodman, Malcolm Norwegian Univ Sci & Technol Dept Engn Cybernet NO-7491 Trondheim Norway BP Explorat Operating Co Ltd Sunbury On Thames TW16 7BP Middx England

A general modelling framework for optimization of multiphase flow networks with discrete decision variables is presented. The framework is expressed with the graph and special attention is given to the convexity properties of the mathematical programming formulation that follows. nonlinear pressure and temperature relations are modelled using multivariate splines, resulting in a mixed-integer nonlinear programming (MINLP) formulation with spline constraints. A global solution method is devised by combining the framework with a spline-compatible MINLP solver, recently presented in the literature. The solver is able to globally solve the nonconvex optimization problems. The new solution method is benchmarked with several local optimization methods on a set of three realistic subsea production optimization cases provided by the oil company BP. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： nonlinear flow networks Petroleum production optimization mixed-integer nonlinear programming Branch-and-bound Splines

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