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The interplay between renewables penetration, costing and emissions in the sizing of stand-alone hydrogen systems

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2015年第1期40卷 125-135页

作者： Brka, Adel Al-Abdeli, Yasir M. Kothapalli, Ganesh Edith Cowan Univ Sch Engn Joondalup WA 6027 Australia

multi-objective genetic algorithms are used to optimise three stand-alone hydrogen systems (WG-H-2, WG/PV-H-2 and PV-H-2) under three different objective functions: minimising (hardware) Net Present Cost - NPC ($), whole Life Cycle Emissions - LCE (CO2-eq/yr) and dumped/Excess Energy -EE (%) at low demand. Optimisations considering Excess Energy haven't been reported before. Simulations are implemented using MATLAB, incorporate experimentally resolved fuel cell start-up transients, and dynamic profiles for wind speed, solar irradiance as well as electric load demand. Results indicate the significance of integrating fuel cell start-up into the LPSP when optimising systems, another aspect not reported before and a modified LPSP is introduced. Furthermore, when sizing energy systems by reducing LCE, EE, and NPC, the favoured hybrid architecture appears to be WG-H-2 over the others studied. For the same LPSP, an interesting finding is that increased renewables penetration (reduced dumped loads) affects the optimised solution but comes at a cost. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Hydrogen energy Systems optimization multi-objective genetic algorithm Experiments Transient start-up Life cycle emissions

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Time-Cost Trade-off Problem under Uncertainty Incorporating multi-objective genetic algorithm and Fuzzy Sets Theory

Time-Cost Trade-off Problem under Uncertainty Incorporating ...

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第17届工业工程与工程管理国际学术会议(IE&EM2010)

作者： S.Fujimura Graduate School of Information Production and SystemsWaseda UniversityKitakyusyuJapan

The time-cost trade-off problem(TCTP) is an important branch in the project scheduling problem. However,the duration and cost of each activity could change stochastically as a result of uncertain *** meet the needs of real projects,an improved approach based on trapezoid fuzzy numbers is applied to estimate the uncertainty of time and *** thenα-cut method is applied to decide the risk ***,improved crossover and mutation methods for multi-objective genetic algorithm(MOGA) are used to make a large-scale computation *** efficiency of the proposed approach is verified by comparison with previous researches. In addition,economic analysis skill of finance cost is integrated into the new model to provide greater flexibility to managers when making ***,time-cost tables under different risk levels for case examples are given and the advantages are investigated based on computation results.

关键词： Finance cost Fuzzy sets theory multi-objective genetic algorithm Project scheduling Risk management Time-cost trade-off problem

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Determination of interfacial heat transfer coefficients in a sand mould casting process using an optimised inverse analysis

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APPLIED THERMAL ENGINEERING 2015年 78卷 682-694页

作者： Palumbo, Gianfranco Piglionico, Vito Piccininni, Antonio Guglielmi, Pasquale Sorgente, Donato Tricarico, Luigi Politecn Bari DMMM Bari Italy

Determination of the interface heat transfer coefficients in casting processes represents a fundamental step in the creation of a reliable numerical model that can predict some of the most common defects (for example hot tear or residual stress) which may affect the process. This work focuses on the most appropriate methodology to determine the heat transfer coefficients for the numerical modelling of the casting process of a super duplex stainless steel (ASTM A890 Gr. 5A) using a silica sand mould. Experimental instrumented castings were used to acquire (both in the casting and in the sand) temperature changes for a number of points of interest by means of thermocouples;in addition, the entire process was simulated using the finite difference method commercial software package MAGMASOFT((R)) (v. 5.2) in order to calculate the temperature at the same points at any step of the process. Firstly, the most influential input parameters were chosen in order to determine the factors to be investigated using a reduced factorial scheme. Further simulations, in which the value of the chosen factors was changed, made it possible to create response surfaces using as a response variable the value of the mismatch between the experimental and numerical temperature changes in the same points. Finally, the optimisation procedure using a multi-objective genetic algorithm was performed, with the goal of finding optimal values for the input parameters, i.e. those with which the mismatch between experimental and numerical temperature changes is minimised. As confirmed by the numerical simulations using the results of the optimisation procedure, the methodology proposed enabled us to determine the correct values of the input variables for modelling the casting process of the ASTM A890 Gr. 5A. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Super duplex stainless steel (ASTM A890 Gr. 5A) Casting MAGMASoft Interface heat transfer coefficients Response surface multi-objective genetic algorithm

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Theoretical analysis and design optimization of wideband input/output branch waveguide couplers for a sheet beam traveling wave tube

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JOURNAL OF ELECTROMAGNETIC WAVES AND APPLICATIONS 2015年第15期29卷 2002-2013页

作者： Shu, G. X. Wang, J. X. Liu, G. Zheng, Y. Yang, L. Y. Luo, Y. Univ Elect Sci & Technol China Sch Phys Elect Chengdu 610054 Peoples R China Univ Calif Davis Dept Appl Sci Davis CA 95616 USA

The branch waveguide coupler (BWC) with an intrinsically excellent microwave property in an extremely wide frequency range was proposed to build the input/output (I/O) structure for the sheet beam traveling wave tube. The odd and even mode theory is utilized to analyze the BWC. Based on the theory, a code is written to calculate its microwave performance parameters. The numerical calculation has a good agreement with the computation simulation. To improve the efficiency of developing the BWC, a novel design optimization approach based on the MATLAB optimization tool is proposed. A BWC with nine branch waveguides is optimized using multi-objective genetic algorithm. In addition to the excellent microwave property, a compact configuration is achieved. It is predicted that the I/O structure possesses a very good performance with coupling above -0.3dB, port reflectivity under -19dB, and isolation less than -15dB in a broad frequency range of 37.4-51.0GHz, corresponding to a bandwidth of 13.6GHz (30.7%).

关键词： sheet beam traveling wave tubes input output structure multi-objective genetic algorithm odd and even mode theory branch waveguide coupler wideband coupler

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Influence of solution heat treatment on mechanical response and fracture behaviour of aluminium alloy sheets: An experimental study

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MATERIALS & DESIGN 2015年 88卷 1119-1126页

作者： Ma, Wenyu Wang, Baoyu Yang, Lei Tang, Xuefeng Xiao, Wenchao Zhou, Jing Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China

Solution heat treatment (SHT), as a part of a consolidated process involving quenching and artificial ageing, significantly affects the mechanical properties of AA6082 sheets. In this study, SHT temperature and time were analysed as main design variables. Specimens were subjected to SHT by using central composite design and then processed by water quenching and artificial ageing (190 degrees C/3 h). Tension tests were conducted at room temperature to measure the tensile strength and formability of the specimens. Response surface models for ultimate tensile stress (UTS) and ductility were constructed as a function of the design variables. UTS generally increased and ductility decreased with increasing SHT temperature and time. This result was processed using the multiobjective sorting genetic algorithm NSGA-II to optimise design parameters and improve UTS and ductility. Pareto optimal solutions corresponding to UTS and ductility and appropriate ranges of design variables were obtained. The fracture characteristics of the alloy parts formed after tensile tests were further analysed using scanning electron microscopy. The fracture mode was the ductile fracture. Increasing SHT temperature and time made the dimples to be shallow and less. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Aluminium alloy Solution heat treatment Response surface model multi-objective genetic algorithm Fracture morphology

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A real-time forecasting model for the spatial distribution of typhoon rainfall

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JOURNAL OF HYDROLOGY 2015年 521卷 302-313页

作者： Lin, Gwo-Fong Jhong, Bing-Chen Natl Taiwan Univ Dept Civil Engn Taipei 10617 Taiwan

Accurate forecasts of hourly rainfall are necessary for early warning systems during typhoons. In this paper, a typhoon rainfall forecasting model is proposed to yield 1- to 6-h ahead forecasts of hourly rainfall. First, an input optimization step integrating multi-objective genetic algorithm (MOGA) with support vector machine (SVM) is developed to identify the optimal input combinations. Second, based on the results of the first step, the forecasted rainfall from each station is used to obtain the spatial characteristics of the rainfall process is presented. An actual application to Tsengwen river basin is conducted to demonstrate the advantage of the proposed model. The results clearly indicate that the proposed model effectively improves the forecasting performance and decreases the negative impact of increasing forecast lead time. The optimal input combinations can be obtained from the proposed model for different stations with different geographical conditions. In addition, the proposed model is capable of producing more acceptable the results of rainfall maps than other model. In conclusion, the proposed modeling technique is useful to improve the hourly typhoon rainfall forecasting and is expected to be helpful to support disaster warning systems. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Hourly typhoon rainfall forecasting Spatial characteristics Meteorological data multi-objective genetic algorithm Support vector machine

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multi-objective optimization for RNA design with multiple target secondary structures

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BMC BIOINFORMATICS 2015年第1期16卷 1-20页

作者： Taneda, Akito Hirosaki Univ Grad Sch Sci & Technol Hirosaki Aomori Japan

Background: RNAs are attractive molecules as the biological parts for synthetic biology. In particular, the ability of conformational changes, which can be encoded in designer RNAs, enables us to create multistable molecular switches that function in biological circuits. Although various algorithms for designing such RNA switches have been proposed, the previous algorithms optimize the RNA sequences against the weighted sum of objective functions, where empirical weights among objective functions are used. In addition, an RNA design algorithm for multiple pseudoknot targets is currently not available. Results: We developed a novel computational tool for automatically designing RNA sequences which fold into multiple target secondary structures. Our algorithm designs RNA sequences based on multi-objective genetic algorithm, by which we can explore the RNA sequences having good objective function values without empirical weight parameters among the objective functions. Our algorithm has great flexibility by virtue of this weight-free nature. We benchmarked our multi-target RNA design algorithm with the datasets of two, three, and four target structures and found that our algorithm shows better or comparable design performances compared with the previous algorithms, RNAdesign and Frnakenstein. In addition to the benchmarks with pseudoknot-free datasets, we benchmarked MODENA with two-target pseudoknot datasets and found that MODENA can design the RNAs which have the target pseudoknotted secondary structures whose free energies are close to the lowest free energy. Moreover, we applied our algorithm to a ribozyme-based ON-switch which takes a ribozyme-inactive secondary structure when the theophylline aptamer structure is assumed. Conclusions: Currently, MODENA is the only RNA design software which can be applied to multiple pseudoknot targets. Successful design results for the multiple targets and an RNA device indicate usefulness of our multi-objective RNA design algori

关键词： RNA switch Artificial riboswitch multi-objective genetic algorithm Pseudoknot

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Evolutionary algorithm-based multi-objective task scheduling optimization model in cloud environments

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WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS 2015年第6期18卷 1737-1757页

作者： Ramezani, Fahimeh Lu, Jie Taheri, Javid Hussain, Farookh Khadeer Univ Technol Sydney Decis Support & E Serv Intelligence Lab Ctr Quantum Computat & Intelligent Syst Sch SoftwareFac Engn & Informat Technol Sydney NSW 2007 Australia Univ Sydney Sch Informat Technol Ctr Distributed & High Performance Comp Sydney NSW 2006 Australia

Optimizing task scheduling in a distributed heterogeneous computing environment, which is a nonlinear multi-objective NP-hard problem, plays a critical role in decreasing service response time and cost, and boosting Quality of Service (QoS). This paper, considers four conflicting objectives, namely minimizing task transfer time, task execution cost, power consumption, and task queue length, to develop a comprehensive multi-objective optimization model for task scheduling. This model reduces costs from both the customer and provider perspectives by considering execution and power cost. We evaluate our model by applying two multi-objective evolutionary algorithms, namely multi-objective Particle Swarm Optimization (MOPSO) and multi-objective genetic algorithm (MOGA). To implement the proposed model, we extend the Cloudsim toolkit by using MOPSO and MOGA as its task scheduling algorithms which determine the optimal task arrangement among VMs. The simulation results show that the proposed multi-objective model finds optimal trade-off solutions amongst the four conflicting objectives, which significantly reduces the job response time and makespan. This model not only increases QoS but also decreases the cost to providers. From our experimentation results, we find that MOPSO is a faster and more accurate evolutionary algorithm than MOGA for solving such problems.

关键词： Cloud computing Task scheduling multi-objective particle swarm optimization multi-objective genetic algorithm Jswarm Cloudsim

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A Knee-Point Based NSAG-Ⅱ for Urban Tourism Path Planning

A Knee-Point Based NSAG-Ⅱ for Urban Tourism Path Planning

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2016战略管理国际会议

作者： Zhang Zhenzhong Ge Peng Ren Peiyu Zheng Weimin Liao Zhixue Business school Sichuan University

With the rapid development of tourism, people begin to pursue personalized and experience-oriented travelling ways. These new demands can be satisfied by the tourist route optimization with tourist preference, which is also an important way to improve tourist satisfaction and increase the competitiveness of scenic spots. Therefore how to provide tourist an optimum route is an important concern both for scenic manager and tourists. In order to provide the best tourism route for tourists, this paper firstly builds a multi-objective optimization model which takes minimum cost and maximum revenue as two objectives of this model. Furthermore, a knee-point based NSAG-Ⅱ was designed as solution methods.

关键词： tourism route multi-objective optimization model multi-objective genetic algorithm tourist preference

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multi-objective Optimization of Different Management Scenarios to Control Seawater Intrusion in Coastal Aquifers

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WATER RESOURCES MANAGEMENT 2015年第6期29卷 1843-1857页

作者： Javadi, Akbar Hussain, Mohammed Sherif, Mohsen Farmani, Raziyeh Univ Exeter Sch Engn Comp Sci & Math Exeter EX4 4QF Devon England UAE Univ Civil & Environm Engn Dept Fac Engn Al Ain U Arab Emirates

Seawater intrusion (SWI) is a widespread environmental problem, particularly in arid and semi-arid coastal areas. Therefore, appropriate management strategies should be implemented in coastal aquifers to control SWI with acceptable limits of economic and environmental costs. This paper presents the results of an investigation on the efficiencies of different management scenarios for controlling saltwater intrusion using a simulation-optimization approach. A new methodology is proposed to control SWI in coastal aquifers. The proposed method is based on a combination of abstraction of saline water near shoreline, desalination of the abstracted water for domestic consumption and recharge of the aquifer by deep injection of the treated wastewater to ensure the sustainability of the aquifer. The efficiency of the proposed method is investigated in terms of water quality and capital and maintenance costs in comparison with other scenarios of groundwater management. A multi-objective genetic algorithm based evolutionary optimization model is integrated with the numerical simulation model to search for optimal solution of each scenario of SWI control. The main objective is to minimize both the total cost of management process and the total salinity in aquifer. The results indicate that the proposed method is efficient in controlling SWI as it offers the least cost and least salinity in the aquifer.

关键词： Seawater intrusion Simulation-optimization multi-objective genetic algorithm Treated wastewater Management scenarios

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