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Using multiobjective mathematical programming to link national competitiveness, productivity, and innovation

ANNALS OF OPERATIONS RESEARCH 2016年第2期247卷 635-655页

作者： Carayannis, Elias G. Grigoroudis, Evangelos George Washington Univ Sch Business 2201 G St NWDuques Hall Washington DC 20052 USA Tech Univ Crete Sch Prod Engn & Management Univ Campus Kounoupidiana 73100 Chania Greece

Innovation-driven competitiveness is critical for a country's long run economic performance in today's knowledge-based global economy. Although several alternative measures of innovation, productivity, and competitiveness have been proposed, these concepts are inherently linked and this justifies the necessity of studying them in an integrated way, giving emphasis on their potential interrelations. This paper proposes a methodological measurement framework based on multiobjective mathematical programming in order to study the linkage among national innovation, productivity, and competitiveness and discover potential performance patterns. The model is applied in a set of European countries for the period 1998-2008. The empirical results reveal important gaps and show that innovativeness, income, and geographic area significantly affect national performances.

关键词： Innovation Productivity Competitiveness multiobjective mathematical programming

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Enhancing Corrected Transient Energy Margin in Electricity Energy Market Operation Using Stochastic multiobjective mathematical programming

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IEEE SYSTEMS JOURNAL 2015年第4期9卷 1419-1429页

作者： Aghaei, Jamshid Mahboubi-Moghaddam, Esmaeil Muttaqi, Kashem M. Shiraz Univ Technol Dept Elect & Elect Engn Shiraz 71454 Iran Univ Wollongong Sch Elect Comp & Telecommun Engn Australian Power Qual & Reliabil Ctr Wollongong NSW 2522 Australia

In this paper, a new stochastic multiobjective model for the market clearing of the joint energy and reserve auctions is proposed wherein both supply and demand sides can participate as reserves. The proposed framework considers the dynamic security aspect of the power system in the scenario-based market operation. To solve the problem, first, on the basis of lattice Monte Carlo simulation, different scenarios are generated to model the uncertainties of power system (including generating units and transmission line contingencies). Then, the competing objective functions of the proposed framework, including the expected social welfare function and expected corrected transient energy margin (CTEM), are simultaneously optimized for each scenario in the multiobjective framework. To calculate the CTEM, a sensitivity analysis based on the ac power flow formulation is incorporated before solving the optimization problem of the market clearing. The optimization problem is solved considering dc power flow constraints and system reserve requirements. Eventually, the scenarios are aggregated based on the expected value of decision variables to produce the final results of the market clearing framework. The model is applied to the New England test system, and simulation studies are implemented to demonstrate the effectiveness of the proposed method.

关键词： Corrected transient energy margin (CTEM) Monte Carlo simulation market clearing multiobjective mathematical programming stochastic framework

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Optimality conditions and duality for mathematical programming with equilibrium constraints including multiple interval-valued objective functions on Hadamard manifolds

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JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS 2024年第2期41卷 1105-1136页

作者： Tung, L. T. Singh, V. Can Tho Univ Coll Nat Sci Dept Math Can Tho 900000 Vietnam Natl Inst Technol Mizoram Dept Math Aizawl 796012 Mizoram India

This paper investigates mathematical programming with equilibrium constraints including multiple interval-valued objective functions on Hadamard manifolds. In the first part, both necessary and sufficient optimality conditions for some types of efficient solutions are considered. After that, the Wolfe and Mond-Weir type dual problems are formulated and the duality relations under geodesic convexity assumptions are examined. Some examples are proposed to illustrate the results.

关键词： multiobjective mathematical programming Equilibrium constraints Interval-valued objective functions Hadamard manifolds Karush-Kuhn-Tucker optimality conditions Mond-Weir and Wolfe duality

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multiobjective portfolio optimization: bridging mathematical theory with asset management practice

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ANNALS OF OPERATIONS RESEARCH 2018年第1-2期267卷 585-606页

作者： Xidonas, Panos Hassapis, Christis Mavrotas, George Staikouras, Christos Zopounidis, Constantin ESSCA Grande Ecole Paris France Univ Cyprus Nicosia Cyprus Natl Tech Univ Athens Athens Greece Athens Univ Econ & Business Athens Greece Audencia Business Sch Nantes France

We attempt to establish an integrated portfolio optimization business framework, in order to bridge the underlying gap between the complex mathematical theory of multiobjective mathematical programming and asset management practice. Our aim is to assist practitioners and portfolio managers in formulating successful investment strategies, by providing them with an effective decision support tool. In particular, we propose a multiobjective portfolio model, able to support the simultaneous optimization of multiple investment objectives. We also manage to integrate a set of sophisticated real-world non-convex investment policy limitations, such as the cardinality constraints, the buy-in thresholds, the transaction costs, along with particular normative rules. The underlying investment management rationale of the proposed managerial protocol is displayed through an illustrative business flowchart, while we also provide an analytical step-by-step portfolio management business routine. The validity of the model is verified through an extended empirical testing application on the Eurostoxx 50. According to the results, a sufficient number of efficient or Pareto optimal portfolios produced by the model, appear to possess superior out-of-sample returns with respect to the underlying benchmark.

关键词： Portfolio optimization multiobjective mathematical programming Asset management Eurostoxx 50

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Stochastic Wind-thermal Generation Scheduling Considering Emission Reduction: A multiobjective mathematical programming Approach

Stochastic Wind-thermal Generation Scheduling Considering Em...

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Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Khorsand, M. A. Zakariazadeh, A. Jadid, S. Iran Univ Sci & Technol IUST Ctr Excellence Power Syst Automat & Operat Dept Elect Engn Tehran Iran

ISBN: (纸本)9781424462551

To regard environmental protection renewable energy sources especially wind, has been applied to achieve emission reduction goals. While wind generation does not directly produce air pollutants emission, it causes some changes on thermal power generation scheduling which may lead them to produce more air pollutants emission especially during low and medium energy demand periods. So it seems necessary to consider air pollutants emission level in wind-thermal scheduling problems. This paper proposes a methodology for wind-thermal scheduling in a power system with high penetration of wind power subject to consider air pollutants emission reduction. Because of simultaneous minimizing total operating cost and air pollutants emission, a multiobjective mathematical programming (MMP) is introduced. The computation of the required reserve levels and their costs is attained through a stochastic programming market-clearing model. Also, the network constraints and the costs of both the load shedding and the wind spillage are considered. The usefulness of the proposed approach was tested through an IEEE 30-bus test system.

关键词： Air Pollutants Emission multiobjective mathematical programming Stochastic programming Unit Commitment Wind Power

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Equity portfolio construction and selection using multiobjective mathematical programming

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JOURNAL OF GLOBAL OPTIMIZATION 2010年第2期47卷 185-209页

作者： Xidonas, Panagiotis Mavrotas, George Psarras, John Natl Tech Univ Athens Athens Greece

A multi-objective mixed integer programming model for equity portfolio construction and selection is developed in this study, in order to generate the Pareto optimal portfolios, using a novel version of the well known epsilon-constraint method. Subsequently, an interactive filtering process is also proposed to assist the decision maker in making his/her final choice among the Pareto solutions. The proposed methodology is tested through an application in the Athens Stock Exchange.

关键词： Portfolio optimization multiobjective mathematical programming epsilon-Constraint method Equities

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Joint economic and emission dispatch in energy markets: A multiobjective mathematical programming approach

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ENERGY 2010年第3期35卷 1497-1504页

作者： Vahidinasab, V. Jadid, S. Iran Univ Sci & Technol Dept Elect Engn Ctr Excellence Power Syst Automat & Operat Tehran 16844 Iran

Economic load dispatch is the method of determining the most efficient, low-cost and reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. Environmental concerns that arise due to the operation of fossil fuel fired electric generators, change the classical problem into multiobjective emission/economic dispatch (MEED) which is formulated as a constrained nonlinear multiobjective mathematical programming (MMP). The proposed MEED formulation includes emission minimization objective, AC load flow constraints and security constraints of the power system which usually are found simultaneously in real-world power systems. The proposed model has a more accurate evaluation of transmission losses obtained from the load flow equations. The MMP approach based on c-constraint algorithm has been proposed for generating Pareto-optimal solutions of power systems MEED problem. Moreover, fuzzy decision making process is employed to extract one of the Pareto-optimal solutions as the best compromise nondominated solution. The proposed approach is simulated on the IEEE 30-bus six-generator test system and obtained results have been comprehensively compared with some of the most recently published research in the area (from the both aspects of precision and execution tome) which confirms the potential and effectiveness of the proposed approach. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Electricity market Emission/economic load dispatch multiobjective mathematical programming Emission control

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Stochastic Wind-thermal Generation Scheduling Considering Emission Reduction: A multiobjective mathematical programming Approach

Stochastic Wind-thermal Generation Scheduling Considering Em...

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Asia-Pacific Power and Energy Engineering Conference

作者： M. A. Khorsand A. Zakariazadeh S. Jadid Center of Excellence for Power System Automation and Operation Electrical Engineering Department Iran University of Science and Technology (IUST)

ISBN: (纸本)9781424462537

关键词： Air Pollutants Emission multiobjective mathematical programming Stochastic programming Unit Commitment Wind Power

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Uncertainty management in multiobjective hydro-thermal self-scheduling under emission considerations

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APPLIED SOFT COMPUTING 2015年 37卷 737-750页

作者： Aghaei, Jamshid Ahmadi, Abdollah Rabiee, Abdorreza Agelidis, Vassilios G. Muttaqi, Kashem M. Shayanfar, H. A. Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Univ New S Wales Australian Energy Res Inst Sydney NSW 2052 Australia Univ New S Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia Shahrekord Univ Fac Engn & Technol Dept Elect Engn Shahrekord Iran Univ Wollongong Australian Power Qual & Reliabil Ctr Sch Elect Comp & Telecommun Engn Wollongong NSW Australia Iran Univ Sci & Technol Dept Elect Engn Ctr Excellence Power Syst Automat & Operat Tehran Iran

In this paper, a stochastic multiobjective framework is proposed for a day-ahead short-term Hydro Thermal Self-Scheduling (HTSS) problem for joint energy and reserve markets. An efficient linear formulations are introduced in this paper to deal with the nonlinearity of original problem due to the dynamic ramp rate limits, prohibited operating zones, operating services of thermal plants, multi-head power discharge characteristics of hydro generating units and spillage of reservoirs. Besides, system uncertainties including the generating units' contingencies and price uncertainty are explicitly considered in the stochastic market clearing scheme. For the stochastic modeling of probable multiobjective optimization scenarios, a lattice Monte Carlo simulation has been adopted to have a better coverage of the system uncertainty spectrum. Consequently, the resulting multiobjective optimization scenarios should concurrently optimize competing objective functions including GENeration COmpany's (GENCO's) profit maximization and thermal units' emission minimization. Accordingly, the epsilon-constraint method is used to solve the multiobjective optimization problem and generate the Pareto set. Then, a fuzzy satisfying method is employed to choose the most preferred solution among all Pareto optimal solutions. The performance of the presented method is verified in different case studies. The results obtained from epsilon-constraint method is compared with those reported by weighted sum method, evolutionary programming-based interactive Fuzzy satisfying method, differential evolution, quantum-behaved particle swarm optimization and hybrid multi-objective cultural algorithm, verifying the superiority of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Stochastic programming Hydro-thermal self scheduling Price uncertainty Generating unit contingency multiobjective mathematical programming

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On the application of plug-in hybrid electric vehicle to compensate network harmonics: A multiobjective approach

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SCIENTIA IRANICA 2014年第6期21卷 2177-2185页

作者： Farahani, H. Feshki Khalili, M. Rabiee, A. Ghazizadeh, M. S. Islamic Azad Univ Ashtian Branch Dept Elect Engn Ashtian Iran Power & Water Univ Technol Tehran Iran Shahrekord Univ Dept Elect Engn Shahrekord Iran

One of the important capabilities of Plug in Hybrid Electric Vehicles (PHEVs) is the injecting/absorbing of harmonic current to/from the grid. In this paper, a multiobjective framework is proposed to improve the power quality of the grid by PHEVs. In this study, each PHEV is modeled as an injected harmonic current source, including different harmonic orders. The objective functions are: Total Harmonic Distortion (THD) of network nodes and the Total PHEV Current (TPC) index, both to be minimized. The multiobjective optimization problem is solved using the epsilon-constraint method. The best compromise solution among various non-dominated (Pareto optimal) solutions is chosen based on a fuzzy approach. A typical 14-node microgrid test system is considered in the case study to examine the effectiveness of the proposed method. (C) 2014 Sharif University of Technology. All rights reserved.

关键词： Plug-In Hybrid Electric Vehicle multiobjective mathematical programming Harmonic Compensating Total Harmonic Distortion (THD) Total PHEV Current (TPC)

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