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Optimization for design and operation of natural gas transmission networks

APPLIED ENERGY 2014年 133卷 56-69页

作者： Uester, Halit Dilaveroglu, Sebnem Texas A&M Univ Dept Ind & Syst Engn College Stn TX 77843 USA BOTAS Petr Pipeline Corp Ankara Turkey

We consider the problem of designing a new natural gas transmission network or expanding an existing network while minimizing the total investment and operating costs. We develop an integrated large-scale mixed-integer nonlinear optimization model to determine pipelines in the network, compressor stations and their capacities, timings of these installations in a multi-period planning horizon, and natural gas purchase and steady-state flow decisions for each period in the network. The model is solvable using state-of-the-art solution methodologies available online. Employing our modeling and the solution methodology for its solution, we conduct computational studies on various test instances generated using realistic network structure and data based on the natural gas network in Turkey as well as data from literature. Our analysis provides insights into sensitivity of network configuration and operations to the number of periods within the planning horizon and cost parameters as well as into strategic decision making for design and expansion of natural gas networks. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Natural gas Network design Multi-period planning mixed-integer nonlinear programming

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Linearization-based algorithms for mixed-integer nonlinear programs with convex continuous relaxation

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JOURNAL OF GLOBAL OPTIMIZATION 2014年第2-3期59卷 343-365页

作者： Hamzeei, Mahdi Luedtke, James Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA

We present two linearization-based algorithms for mixed-integer nonlinear programs (MINLPs) having a convex continuous relaxation. The key feature of these algorithms is that, in contrast to most existing linearization-based algorithms for convex MINLPs, they do not require the continuous relaxation to be defined by convex nonlinear functions. For example, these algorithms can solve to global optimality MINLPs with constraints defined by quasiconvex functions. The first algorithm is a slightly modified version of the LP/NLP-based branch-and-bouund algorithm of Quesada and Grossmann, and is closely related to an algorithm recently proposed by Bonami et al. (Math Program 119:331-352, 2009). The second algorithm is a hybrid between this algorithm and nonlinear programming based branch-and-bound. Computational experiments indicate that the modified LP/NLP-BB method has comparable performance to LP/NLP-BB on instances defined by convex functions. Thus, this algorithm has the potential to solve a wider class of MINLP instances without sacrificing performance.

关键词： mixed-integer nonlinear programming Quasiconvex function Outer approximation

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Design and analysis of demand-adapted railway timetables

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JOURNAL OF ADVANCED TRANSPORTATION 2014年第2期48卷 119-137页

作者： Canca, David Barrena, Eva Algaba, Encarnacion Zarzo, Alejandro Univ Seville Escuela Tecn Super Ingn Seville 41092 Spain Univ Politecn Madrid ETSII Escuela Tecn Super Ingn Ind E-28006 Madrid Spain

Railway scheduling and timetabling are common stages in the classical hierarchical railway planning process and they perhaps represent the step with major influence on user's perception about quality of service. This aspect, in conjunction with their contribution to service profitability, makes them a widely studied topic in the literature, where, nowadays, many efforts are focused on improving the solving methods of the corresponding optimization problems. However, literature about models considering detailed descriptions of passenger demand is sparse. This paper tackles the problem of timetable determination by means of building and solving a nonlinear integer programming model that fits the arrival and departure train times to a dynamic behavior of demand. The optimization model results are then used for computing several measures to characterize the quality of the obtained timetables considering jointly both user and company points of view. Some aspects are discussed, including the influence of train capacity and the validity of Random Incidence Theorem. An application to the C5 line of Madrid rapid transit system is presented. Different measures are analyzed in order to improve the insight into the proposed model and analyze in advance the influence of different objectives on the resulting timetable. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： train timetabling quality of service variable demand mixed-integer nonlinear programming

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Biobjective optimization for general oil field development

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2014年 119卷 123-138页

作者： Isebor, Obiajulu J. Durlofsky, Louis J. Stanford Univ Dept Energy Resources Engn Stanford CA 94305 USA

The optimization of oil field development and production planning typically requires the consideration of multiple, possibly conflicting, objectives. For example, in a waterflooding project, we might seek to maximize oil recovery and minimize water injection. It is therefore important to devise and test optimization procedures that consider two or more objectives in the determination of optimal development and production plans. In this work we present an approach for field development optimization with two objectives. A single-objective product formulation, which systematically combines the two objectives in a sequence of single-objective optimization problems, is applied. The method, called BiPSOMADS, utilizes at its core our recently developed PSO-MADS (Particle Swarm Optimization-Mesh Adaptive Direct Search) hybrid optimization algorithm. This derivative-free procedure has been shown to be effective for the solution of generalized field development and well control problems that include categorical, discrete and continuous variables along with general (nonlinear) constraints. Four biobjective field development and well control examples are solved using BiPSOMADS. These examples include problems that consider the maximization of both net present value and cumulative oil production, and the maximization of both long-term and short-term reservoir performance. An example that highlights the applicability of biobjective optimization for field development under geological uncertainty is also presented. This usage of BiPSOMADS enables us to maximize expected reservoir performance while reducing the risk associated with the worst-case scenario. (C) 2014 Elsevier B.V. All rights reserved.

关键词： biobjective optimization derivative-free optimization petroleum field development mixed-integer nonlinear programming multiobjective programming optimization under uncertainty

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Liner ship route schedule design with port time windows

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2014年 41卷 1-17页

作者： Wang, Shuaian Alharbi, Abdurahim Davy, Pam Univ Wollongong Sch Math & Appl Stat Wollongong NSW 2522 Australia

This paper examines a practical tactical liner ship route schedule design problem, which is the determination of the arrival and departure time at each port of call on the ship route. When designing the schedule, the availability of each port in a week, i.e., port time window, is incorporated. As a result, the designed schedule can be applied in practice without or with only minimum revisions. This problem is formulated as a mixed-integer nonlinear nonconvex optimization model. In view of the problem structure, an efficient holistic solution approach is proposed to obtain global optimal solution. The proposed solution method is applied to a trans-Atlantic ship route. The results demonstrate that the port time windows, port handling efficiency, bunker price and unit inventory cost all affect the total cost of a ship route, the optimal number of ships to deploy, and the optimal schedule. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Container liner shipping Schedule design Containership scheduling Port time windows mixed-integer nonlinear programming

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Strong-branching inequalities for convex mixed integer nonlinear programs

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2014年第3期59卷 639-665页

作者： Kilinc, Mustafa Linderoth, Jeff Luedtke, James Miller, Andrew Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA United Parcel Serv Atlanta GA 30328 USA

Strong branching is an effective branching technique that can significantly reduce the size of the branch-and-bound tree for solving mixed integer nonlinear programming (MINLP) problems. The focus of this paper is to demonstrate how to effectively use "discarded" information from strong branching to strengthen relaxations of MINLP problems. Valid inequalities such as branching-based linearizations, various forms of disjunctive inequalities, and mixing-type inequalities are all discussed. The inequalities span a spectrum from those that require almost no extra effort to compute to those that require the solution of an additional linear program. In the end, we perform an extensive computational study to measure the impact of each of our proposed techniques. Computational results reveal that existing algorithms can be significantly improved by leveraging the information generated as a byproduct of strong branching in the form of valid inequalities.

关键词： mixed-integer nonlinear programming Strong-branching Disjunctive inequalities Mixing inequalities

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Global optimization of general non-convex problems with intermediate bilinear substructures

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OPTIMIZATION METHODS & SOFTWARE 2014年第3期29卷 442-462页

作者： Zorn, Keith Sahinidis, Nikolaos V. Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

This work considers the global optimization of general non-convex nonlinear and mixed-integer nonlinear programming (MINLP) problems with underlying bilinear substructures. We combine reformulation-linearization techniques and advanced convex envelope construction techniques to produce tight subproblem formulations for these underlying structures. When incorporated as linear cutting planes, these relaxation strengthening strategies are highly effective at tightening standard linear programming relaxations generated by factorable programming techniques. Because the size of these augmented linear relaxations increases exponentially with the number of variables, we employ cut filtering and selection strategies to ensure that the tightened subproblems are solved efficiently. We introduce algorithms for bilinear substructure detection, cutting plane identification, cut filtering, and cut selection and embed the proposed implementation in Branch-and-Reduce Optimization Navigator at every node in the branch-and-bound tree. A computational study including problem instances from standard literature test libraries is included to assess the performance of the proposed implementation. Results show that underlying bilinear substructures are identified in 30% of the problems in GLOBALLib and MINLPLib and that the exploitation of these structures significantly reduces computational time, branch-and-bound tree size, and required memory.

关键词： branch-and-bound global optimization factorable polyhedral relaxation reformulation-linearization techniques mixed-integer nonlinear programming

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A mixed-integer nonlinear program for the optimal design and dispatch of distributed generation systems

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OPTIMIZATION AND ENGINEERING 2014年第1期15卷 167-197页

作者： Pruitt, Kristopher A. Leyffer, Sven Newman, Alexandra M. Braun, Robert J. Colorado Sch Mines Div Econ & Business Golden CO 80401 USA Argonne Natl Lab Math & Comp Sci Div Argonne IL 60439 USA Colorado Sch Mines Dept Mech Engn Golden CO 80401 USA

Maturing distributed generation (DG) technologies have promoted interest in alternative sources of energy for commercial building applications due to their potential to supply on-site heat and power at a lower cost and emissions rate compared to centralized generation. Accordingly, we present an optimization model that determines the mix, capacity, and operational schedule of DG technologies that minimize economic and environmental costs subject to the heat and power demands of a building and to the performance characteristics of the technologies. The technologies available to design the system include lead-acid batteries, photovoltaic cells, solid oxide fuel cells, heat exchangers, and a hot water storage tank. Modeling the acquisition and operation of discrete technologies requires integer restrictions, and modeling the variable electric efficiency of the fuel cells and the variable temperature of the tank water introduces nonlinear equality constraints. Thus, our optimization model is a nonconvex, mixed-integer nonlinear programming (MINLP) problem. Given the difficulties associated with solving large, nonconvex MINLPs to global optimality, we present convex underestimation and linearization techniques to bound and solve the problem. The solutions provided by our techniques are close to those provided by existing MINLP solvers for small problem instances. However, our methodology offers the possibility to solve large problem instances that exceed the capacity of existing solvers and that are critical to the real-world application of the model.

关键词： Global optimization mixed-integer nonlinear programming Distributed generation Combined heat and power

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Selecting different raw materials for methanol production using an MINLP model

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JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING 2014年 19卷 221-227页

作者： Kralj, Anita Kovac Univ Maribor Fac Chem & Chem Engn SLO-2000 Maribor Slovenia

This paper aims at selecting different raw materials, using an MINLP (mixed-integer nonlinear programming) model, when considering the usage of more favourable raw materials for methanol production. The best selection of raw material alternatives was sought for methanol production. Methanol is produced from synthesis gas that is produced from different raw materials - natural gas or biogas. The basic starting point when comparing them is the same mass inlet flow rate for both raw materials. Methanol production was simulated for both natural gas or biogas as the raw material, using an Aspen Plus simulator with a real chemical thermodynamic. Methanol production can be enlarged by simultaneous structuring such as selecting the usage of more favourable raw materials, and parameter optimisation using the MINLP. The selection of raw methanol with optimal parameters has the greatest impact on higher methanol production. Optimal methanol conversion can take place during this operation, by applying optimal parametric data within a reformer unit (temperature = 840 degrees C and pressure = 8 bar), using natural gas. The optimal production of methanol from natural gas was 17 510 kg/h under optimal parameters for 8.4% higher production than under existing parameters. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Methanol production Natural gas Biogas Mathematical model mixed-integer nonlinear programming

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Symmetry-exploiting cuts for a class of mixed-0/1 second-order cone programs

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DISCRETE OPTIMIZATION 2014年 13卷 23-35页

作者： Drewes, Sarah Pokutta, Sebastian Georgia Inst Technol ISyE Atlanta GA 30332 USA

We will analyze mixed-0/1 second-order cone programs where the continuous and binary variables are solely coupled via the conic constraints. We devise a cutting-plane framework based on an implicit Sherali-Adams reformulation. The resulting cuts are very effective as symmetric solutions are automatically cut off and each equivalence class of 0/1 solutions is visited at most once. Further, we present computational results showing the effectiveness of our method and briefly sketch an application in optimal pooling of securities. (C) 2014 Elsevier B.V. All rights reserved.

关键词： mixed-integer nonlinear programming Cutting planes Second order cone programming Outer approximation

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