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Multi-parametric MINLP optimization study of a composite I beam floor system

ENGINEERING STRUCTURES 2017年 130卷 316-335页

作者： Kravanja, S. Zula, T. Klansek, U. Univ Maribor Fac Civil Engn Transportat Engn & Architecture Smetanova 17 SI-2000 Maribor Slovenia

This paper deals with a comparative study of an optimal design regarding composite steel and concrete floor structures based on the performed multi-parametric mixed-integer non-linear programming (MINLP) approach, and Eurocode specifications. The optimization models COMBOPT (COMposite Beam OPTimization) were developed and cost optimizations of the structure alternatives were performed. A series of MINLP optimizations were executed over a wide range of various design parameters: different material unit prices, hourly labour costs, imposed loads, structure spans, steel and concrete grades, welded and standard steel sections, plastic and elastic cross-sectional resistances, different positions of the neutral axis and different locations of the centre of gravity axis of the transformed (all steel) section. The Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm was applied. The minimal self-manufacturing costs of the structure, steel and concrete grades and standard sizes were obtained through each individual MINLP optimization. All the results were analysed and compared. Comparative diagrams and a recommended design for a composite floor system were determined. In addition, this study answered some questions regarding the influence of unit prices on the optimal design, the most suitable position of the neutral axis, the competitive spans of the structures with welded and standard steel sections, the competitiveness of the plastic cross-section resistance when compared to the elastic resistance, the spans and loads where the ultimate and the serviceability limit states are predominant and the adequate location of the centre of gravity axis of the transformed (all steel) section. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Composite structures Cost optimization Structure optimization Multi-parametric optimization mixed-integer non-linear programming MINLP

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A convex mathematical program for pump scheduling in a class of branched water networks

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APPLIED ENERGY 2017年第Part2期185卷 1702-1711页

作者： Bonvin, Gratien Demassey, Sophie Le Pape, Claude Maizi, Nadia Mazauric, Vincent Samperio, Alfredo PSL Res Univ Ctr Appl Math MINES ParisTech BP 207 F-06902 Sophia Antipolis France Schneider Elect Strategy & Technol 38TEC F-38050 Grenoble 9 France

We address the day-ahead pump scheduling problem for a class of branched water networks with one pumping station raising water to tanks at different places and levels. This common class is representative of rural drinking water distribution networks, though not exclusively so. Many sophisticated heuristic algorithms have been designed to tackle the challenging general problem. By focusing on a class of networks, we show that a pure model-based approach relying on a tractable mathematical program is pertinent for real-size applications. The practical advantages of this approach are that it produces optimal or near-optimal solutions with performance guarantees in near real-time, and that it is replicable without algorithmic development. We apply the approach to a real drinking water supply system and compare it to the current operational strategy based on historical data. An extensive empirical analysis assesses the financial and practical benefits: (1) it achieves significant savings in terms of operation costs and energy consumption, (2) its robustness to dynamic pricing means that demand-response can be efficiently implemented in this type of energy-intensive utility. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Pump scheduling Branched water networks Demand-response mixed-integer non-linear programming Convex relaxation

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Leveraging smart meter data for economic optimization of residential photovoltaics under existing tariff structures and incentive schemes

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APPLIED ENERGY 2017年第Sep.1期201卷 158-173页

作者： Every, Jeremy Li, Li Dorrell, David G. Univ Technol Sydney Fac Engn & Informat Technol Sch Elect Mech & Mechatron Syst 81 Broadway Ultimo NSW 2007 Australia Univ KwaZulu Natal Coll Agr Engn & Sci Discipline Elect Elect & Comp Engn ZA-4041 Durban South Africa

The introduction of smart grid technologies and the impending removal of incentive schemes is likely to complicate the cost-effective selection and integration of residential PV systems in the future. With the widespread integration of smart meters, consumers can leverage the high temporal resolution of energy consumption data to optimize a PV system based on their individual circumstances. In this article, such an optimization strategy is developed to enable the optimal selection of size, tilt, azimuth and retail electricity plan for a residential PV system based on hourly consumption data. Hourly solar insolation and PV array generation models are presented as the principal components of the underlying objective function. A net present value analysis of the potential monetary savings is considered and set as the optimization objective. A particle swarm optimization algorithm is utilized, modified to include a penalty function in order to handle associated constraints. The optimization problem is applied to real-world Australian consumption data to establish the economic performance and characteristics of the optimized systems. For all customers assessed, an optimized PV system producing a positive economic benefit could be found. However not all investment options were found to be desirable with at most 77.5% of customers yielding an acceptable rate of return. For the customers assessed, the mean PV system size was found to be 2 kW less than the mean size of actual systems installed in the assessed locations during 2015 and 2016. Over-sizing of systems was found to significantly reduce the potential net benefit of residential PV from an investor's perspective. The results presented in this article highlight the necessity for economic performance optimization to be routinely implemented for small-scale residential PV under current regulatory and future smart grid operating environments. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Photovoltaic system Smart meter Dynamic tariff mixed-integer non-linear programming Particle swarm optimization Net present value analysis

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On global optimization with indefinite quadratics

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EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION 2017年第3期5卷 309-337页

作者： Fampa, Marcia Lee, Jon Melo, Wendel Univ Fed Rio de Janeiro Rio De Janeiro Brazil Univ Michigan Ann Arbor MI 48109 USA

We present an algorithmic framework for global optimization problems in which the non-convexity is manifested as an indefinite-quadratic as part of the objective function. Our solution approach consists of applying a spatial branch-and-bound algorithm, exploiting convexity as much as possible, not only convexity in the constraints, but also extracted from the indefinite-quadratic. A preprocessing stage is proposed to split the indefinite-quadratic into a difference of convex quadratic functions, leading to a more efficient spatial branch-and-bound focused on the isolated non-convexity. We investigate several natural possibilities for splitting an indefinite quadratic at the preprocessing stage, and prove the equivalence of some of them. Through computational experiments with our new solver iquad, we analyze how the splitting strategies affect the performance of our algorithm, and find guidelines for choosing amongst them.

关键词： Global optimization Indefinite quadratic Difference of convex functions Eigendecomposition Semidefinite programming mixed-integer non-linear programming

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Data-driven Security-Constrained AC-OPF for Operations and Markets

Data-driven Security-Constrained AC-OPF for Operations and M...

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Power Systems Computation Conference

作者： Lejla Halilbasic Florian Thams Andreas Venzke Spyros Chatzivasileiadis Pierre Pinson Center for Electric Power and Energy Technical University of Denmark Kongens Lyngby Denmark

In this paper, we propose a data-driven preventive security-constrained AC optimal power flow (SC-OPF), which ensures small-signal stability and N-1 security. Our approach can be used by both system and market operators for optimizing redispatch or AC based market-clearing auctions. We derive decision trees from large datasets of operating points, which capture all security requirements and allow to define tractable decision rules that are implemented in the SC-OPF using mixed-integer nonlinear programming (MINLP). We propose a second-order cone relaxation for the non-convex MINLP, which allows us to translate the non-convex and possibly disjoint feasible space of secure system operation to a convex mixed-integer OPF formulation. Our case study shows that the proposed approach increases the feasible space represented in the SC-OPF compared to conventional methods, can identify the global optimum as opposed to tested MINLP solvers and significantly reduces computation time due to a decreased problem size.

关键词： Security-constrained OPF Small-signal stability Convex relaxation mixed-integer non-linear programming

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MINLP optimization of a composite I beam floor system

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STEEL AND COMPOSITE STRUCTURES 2016年第5期22卷 1163-1192页

作者： Zula, Tomaz Kravanja, Stojan Klansek, Uros Univ Maribor Fac Civil Engn Transportat Engn & Architecture Smetanova 17 SLO-2000 Maribor Slovenia

This paper presents the cost optimization of a composite I beam floor system, designed to be made from a reinforced concrete slab and steel I sections. The optimization was performed by the mixed-integer non-linear programming (MINLP) approach. For this purpose, a number of different optimization models were developed that enable different design possibilities such as welded or standard steel I sections, plastic or elastic cross-section resistances, and different positions of the neutral axes. An accurate economic objective function of the self-manufacturing costs was developed and subjected to design, resistance and deflection (in) equality constraints. Dimensioning constraints were defined in accordance with Eurocode 4. The Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm was applied together with a two-phase MINLP strategy. A numerical example of the optimization of a composite I beam floor system, as presented at the end of this paper, demonstrates the applicability of the proposed approach. The optimal result includes the minimal produced costs of the structure, the optimal concrete and steel strengths, and dimensions.

关键词： composite structures cost optimization structural optimization mixed-integer non-linear programming MINLP

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Reduced-order modelling of flexible CCS and assessment using short-term resource scheduling approach

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INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL 2016年第Part2期48卷 253-274页

作者： Alie, Colin Elkamel, Ali Douglas, Peter L. Croiset, Eric Univ Waterloo Dept Chem Engn 200 Univ Ave West Waterloo ON N2L 3G1 Canada

CCS (Carbon Capture and Storage) can allow conventional fuels for electricity generation to be used while achieving deep reductions in GHG ( Greenhouse Gas) emissions at the cost, though, of reduced efficiency and capacity relative to an electricity system without CCS. It has been proposed that the deployment of generating units with CCS that are flexible-in particular, that can moderate their CO2 recovery in response to market conditions-would mitigate some of the disbenefit associated with the technology. This paper uses the short-term resource scheduling approach to assess the value of flexible generating units with CCS (Carbon Capture and Storage);generating unit part-load performance, variability of CO2 recovery, and detailed operation of an electricity system including transmission and reliability constraints are considered simultaneously. A parametric study of the performance of a coal-fired generating unit with CCS is undertaken using an Aspen Plus steady-state model and a reduced-order model representing the Pareto optimal frontier of the unit is developed using regression analysis. The base economic dispatch underlying the electricity system simulator is extended to accommodate flexible generating units with CCS. The flexible generating unit with CCS is added to the IEEE RTS'96 (Institute of Electrical and Electronics Engineers One-Area Reliability Test System-1996) and the operation of the modified IEEE RTS'96 is simulated for one week. The results are contrasted with results taken from Alin et al, (2015) for the base IEEE RTS'96 and an IEEE RTS'96 with "fixed" CCS. "Flexible" CCS is effective at reducing GHG emissions, though to a slightly lesser extent than was observed via "fixed" CCS. However, with GHG regulation in place, flexibility markedly increases the net energy benefit of the generating unit with CCS and this was achieved not through adjustment of CO2 recovery in order to moderate output but, rather, by increasing the generating unit's ability

关键词： Process simulation Energy Environmental engineering Optimization Post-combustion CO2 capture Carbon Capture and Storage GHG mitigation mixed-integer non-linear programming Short-term resource scheduling surrogate model Reduced-order model

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A hybrid MILP-LP-LP approach for the optimal design and operation of unconfined groundwater utilization systems

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JOURNAL OF WATER SUPPLY RESEARCH AND TECHNOLOGY-AQUA 2016年第3期65卷 208-219页

作者： Bostan, M. Afshar, M. H. Khadem, M. Akhtari, A. A. Islamic Azad Univ Kermanshah Branch Coll Agr Dept Civil Engn POB *** Kermanshah Iran Iran Univ Sci & Technol Civil Engn Fac POB 16765-163 Tehran Iran Iran Univ Sci & Technol Envirohydroinformat COE POB 16765-163 Tehran Iran Iran Univ Sci & Technol Sch Civil Engn Tehran Iran Razi Univ Coll Engn Dept Civil Engn POB *** Kermanshah Iran

This paper proposes a hybrid mixed-integer linear programming-linear programming-linear programming (MILP-LP-LP) methodology for simultaneous optimal design and operation of unconfined groundwater utilization systems. The proposed model is an extension to the earlier LP-LP model introduced by the authors for the optimal design and operation of confined groundwater utilization systems. The proposed model can be used to minimize the total cost, including the well drilling, pump installation cost and energy cost, of utilizing a two-dimensional unconfined aquifer under both steady-state and transient flow conditions. The solution of the problem is defined by the well numbers and location, well drilling depth and the corresponding pumping rates, satisfying a downstream demand, lower/upper bound on the pumping rates, and lower/upper bound on the water level drawdown in the wells. A discretized version of the differential equation governing the aquifer is first embedded into the model formulation as additional constraints. The resulting mixed-integer non-linear programming problem is then decomposed into three sub-problems with different sets of decision variables, namely, hydraulic head, well numbers and locations and their pumping rates, and well depths. Starting with a set of random values for all decision variables, the three sub-problems are solved assuming fixed values for the other variables. This process is iterated until convergence is achieved.

关键词： decomposition groundwater management mixed-integer non-linear programming operation cost unconfined aquifer

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mixed-integer non-linear programming approach to structural optimization

Mixed-integer non-linear programming approach to structural ...

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11th International Conference on Computer Aided Optimum Design of Structures

作者： Kravanja, S. Univ Maribor Fac Civil Engn SLO-2000 Maribor Slovenia

ISBN: (纸本)9781845641856

The paper presents the mixed-integer non-linear programming (MINLP) approach to structural optimization. MINLP is a combined discrete/continuous optimization technique, where discrete binary 0-1 variables are defined for optimization of discrete alternatives and continuous variables for optimization of parameters. The MINLP optimization is performed through three steps: i.e. the generation of a mechanical superstructure, the modelling of an MINLP model formulation and the solution of the defined MINLP problem. As the discrete/continuous optimization problems are usually non-convex and highly non-linear, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm is applied for the optimization. The accompanied Linked Multilevel Hierarchical Strategy (LMHS) is developed to accelerate the convergence of the mentioned algorithm. Two examples are presented at the end of the paper.

关键词： mixed-integer non-linear programming MINLP structural optimization structural synthesis

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A flow-to-equity approach to coordinate supply chain network planning and financial planning with annual cash outflows to an institutional investor

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Business Research 2016年第2期9卷 297-333页

作者： Steinrücke, Martin Albrecht, Wolfgang Faculty of Law and Economics University of Greifswald Friedrich-Loeffler-Str. 70 Greifswald 17489 Germany

A common side effect of cross-linked global economies is that well-positioned middle class companies are acquired by institutional investors, which formulate unreasonable return expectations in many cases. As a consequence, the resulting payouts are often not in line with business operations so that even world market leaders get into trouble or close down. In this context, we consider the case of a sanitary company, which had to manage the described situation after a business takeover. In order to coordinate the annual cash outflows to the investor with intra-organizational supply chain planning and financial planning, we propose a mixed-integer non-linear programming model that is based on the flow-to-equity discounted cash flow method. The objective is to maximize the present value of equity while determining annual cash outflows to the institutional investor during his engagement. As the decisions of the investor during his engagement influence possible operations of the company after his engagement, the residual value of equity (that influences the selling price) is taken into account. The modeling is based on cash flow series, which result from supply chain operations and restructuring on the one hand, and from financial transactions on the other. Financing is characterized by interest rates depending on the time period the credit starts, the credit period, the debt limit of the company and the current total debt. As the latter is a result of the optimization, non-linearity arises. Nevertheless, both the expected demand scenario and further randomly generated demand scenarios of the sanitary company could be solved to the optimum with the commercial optimization package GAMS 23.8/SCIP 2.1.1 within acceptable computation times, if capacity profiles are assigned to the locations to depict feasible and/or preferred capacity developments. © 2016, The Author(s).

关键词： Annual cash outflows to the investor Capacity profiles Company takeover Flow-to-equity method mixed-integer non-linear programming Supply chain design

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