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Optimal placement of capacitors in distribution systems using an immune multi-objective algorithm

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2008年第3期30卷 184-192页

作者： Huang, Tsong-Liang Hsiao, Ying-Tung Chang, Chih-Han Jiang, Joe-Air Natl Taiwan Univ Dept Bio Ind Mechatron Engn Taipei 106 Taiwan Natl Taipei Univ Educ Dept Comp Sci Taipei 106 Taiwan Tamkang Univ Dept Elect Engn Taipei 106 Taiwan

This work proposes a two-stage immune algorithm that embeds the compromise programming to perform multi-objective optimal capacitor placement. A new problem formulation model that involves fuzzy sets to reflect the imprecise nature of objectives and incorporates multiple planning requirements is presented. The proposed approach finds a set of non-inferior (Pareto) solutions rather than any single aggregated optimal solution. Additionally, this developed approach eliminates the need for any user-defined weight factor to aggregate all objectives. Comparative studies are conducted on an actual system with encouraging results, demonstrating the effectiveness of the proposed approach. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： capacitor placement immune algorithm non-inferior set compromise programming

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Suitability of different precipitation data sources for hydrological analysis: a study from Western Ghats, India

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2022年第2期194卷 1-20页

作者： Reddy, Beeram Satya Narayana Shahanas, P., V Pramada, S. K. Natl Inst Technol Calicut Dept Civil Engn Kozhikode Kerala India

For hydrological analysis, it is essential to have continuous and long-term precipitation data. However, the precipitation data from rain gauge stations are often insufficient and not continuous. At present, ground-based gridded data and satellite-based gridded data are often used as an alternative. However, these data sets have to be evaluated for their suitability in hydrological studies. The current study compared three different rainfall data sources with the observed station data for the Kallada River basin of Kerala, India. The ground-based gridded rainfall data from the India Meteorological Department (IMD), the high-resolution satellite product Tropical Rainfall Measuring Mission (TRMM 3B43, version 7), and the reanalysis data Modern-Era Retrospective Analysis for Research and Applications (MERRA) are used in the analysis. The correlation coefficient, normalized root mean square error, Nash-Sutcliffe efficiency, modified index of agreement, and volumetric efficiency are used as performance indicators. The performance indicator's weights are based on the entropy method. The multi-criteria decision-making techniques like compromise programming and Preference Ranking Organization Method (PROMETHEE II) are used for ranking the precipitation data sources. It is found that IMD ground-based gridded data is ranked 1 among the three data sets. The IMD ground-based gridded data are not homogeneous based on the absolute homogeneity test, even though they had the highest rank. The IMD gridded data are further corrected based on double mass curve analysis. The corrected data were analyzed using the precipitation concentration index (PCI) to assess the temporal variation in precipitation, and it was found that the location falls under a uniform distribution zone.

关键词： Entropy compromise programming PROMETHEE II Performance indicators River basin Precipitation concentration index

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Multi-criteria decision making for integrated urban water management

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WATER RESOURCES MANAGEMENT 2008年第8期22卷 1017-1029页

作者： Zarghami, Mahdi Abrishamchi, Ahmad Ardakanian, Reza Sharif Univ Technol Dept Civil Engn Tehran Iran

The city of Zahedan, in South-eastern Iran, has high population growth, limited local freshwater resources and inadequate water distribution system resulting in water supply failures in recent years. This paper will investigate integration of several demand management measures such as leakage detection on water distribution network, water metering and low volume water fixtures as well as the conjunctive use of surface and groundwater resources of this city. For integration of water management criteria, compromise programming will be used as a multi-objective decision making method. The criteria include minimizing the cost, maximizing water supply and minimizing the social hazards due to the water supply operations. This model will derive optimum long-term plans for implementation of water resources. The results will show that demand management can delay a water transfer project for Zahedan city up to 10 years. compromise programming is as an efficient tool for integrated water resources management in urban areas and the method is capable to being used by decision-makers in other cases.

关键词： compromise programming integrated water resources management long distance water transfer demand management arid regions

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Numerical investigation and optimization of flow and thermal characteristics of nanofluid within a chaotic geometry

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ADVANCED POWDER TECHNOLOGY 2016年第1期27卷 184-192页

作者： Bahiraei, Mehdi Hangi, Morteza Kermanshah Univ Technol Sch Energy Dept Mech Engn Kermanshah Iran Australian Natl Univ Res Sch Engn Canberra ACT 2601 Australia

In this study, hydrothermal characteristics of the water-TiO2 nanofluid are evaluated in the rectangular C-shaped chaotic channel by applying the two-phase Euler-Lagrange method. The results show that the fluid temperature distribution in the C-shaped channel is much more uniform than that in the straight rectangular channel due to the intense mixing in the chaotic geometry. By increasing the concentration and reducing the particle size, both convective heat transfer and pressure drop increase in the chaotic channel. For finer particles, due to more intense particle migration related to the Brownian motion, more uniform concentration distribution is obtained at the channel cross section. The model of mean convective heat transfer coefficient and pressure drop in terms of concentration and particle size was developed by neural network. In order to obtain some cases of the variables (i.e. size and concentration of nanoparticles) in which maximum heat transfer along with minimum pressure drop occurs, optimization on neural network model was implemented using methods of two-objective as well as single-objective (i.e. genetic algorithm coupled with compromise programming decision making method). Eventually, optimum cases were suggested for different importance levels of objective functions. (C) 2015 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.

关键词： Nanofluid Chaotic geometry Genetic algorithm compromise programming Two-phase simulation

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INTERACTIVE compromise HYPERSPHERE METHOD AND ITS APPLICATIONS

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RAIRO-OPERATIONS RESEARCH 2012年第3期46卷 235-252页

作者： Sitarz, Sebastian Univ Silesia Inst Math PL-40007 Katowice Poland

The paper focuses on multi-criteria problems. It presents the interactive compromise hypersphere method with sensitivity analysis as a decision tool in multi-objective programming problems. The method is based on finding a hypersphere (in the criteria space) which is closest to the set of chosen nondominated solutions. The proposed modifications of the compromise hypersphere method are based on using various metrics and analyzing their influence on the original method. Applications of the proposed method are presented in four multi-criteria problems: the assignment problem, the knapsack problem, the project management problem and the manufacturing problem.

关键词： Multi-criteria problems multiple objective linear programming sensitivity analysis decision making compromise programming

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Performance evaluation of CMIP6 climate models for selecting a suitable GCM for future precipitation at different places of Tamil Nadu

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2023年第8期195卷 1-37页

作者： Hemanandhini, S. Rajkumar, L. Vignesh Vellore Inst Technol Sch Civil Engn Dept Environm & Water Resources Engn Vellore 632014 Tamil Nadu India

Climate change refers to long-term variations in climate parameters. Future climate information can be projected using a GCM (General Circulation Model). Identifying a particular GCM is crucial for climate impact studies. Researchers are perplexed about selecting a suitable GCM for downscaling to predict future climate parameters. Recent updates to CMIP6 global climate models have included shared socioeconomic pathways based on the IPCC (Intergovernmental Panel on Climate Change) Sixth Assessment Report (AR6). The performance of 24 CMIP6 GCMs in precipitation with a multi-model ensemble filter was compared to IMD (India Meteorological Department) 0.25 x 0.25 degrees rainfall data in Tamil Nadu. The performance was evaluated with the help of compromise programming (CP), which involves metrics such as R-2 (Pearson correlation co-efficient), PBIAS (Percentage Bias), NRMSE (Normalized Root Mean Square Error), and NSE (Nash-Sutcliffe Efficiency). The GCM ranking was performed through compromise programming by comparing the IMD data and GCM data. The results of the CP analyses of the statistical metrics suggest that the suitable GCMs for the North-East monsoon are CESM2 for Chennai, CAN-ESM5 for Vellore, MIROC6 for Salem, BCC-CSM2-MR for Thiruvannamalai, MPI-ESM-1-2-HAM for Erode, MPI-ESM1-2-LR for Tiruppur, MPI-ESM1-2-LR for Trichy, MPI-ESM1-2-LR for Pondicherry, MPI-ESM1-2-LR for Dindigul, CNRM-CM6-HR for Thanjavur, MPI-ESM1-2-LR for Thirunelveli and UKESM1-0-LL for Thoothukudi. The appropriate suitable GCMs for South-West monsoon as CESM2 is appropriate for Chennai, IPSL-CM6A-LR for Vellore, CESM2-WACCM-FV2 for Salem, CAMS-CSM1-0 for Thiruvannamalai, MPI-ESM-1-2-HR for Erode, MPI-ESM-1-2-HR for Tiruppur, EC- EARTH3 for Trichy, EC- EARTH3 for Pondicherry, MPI-ESM-1-2-HR for Dindigul, CESM2-FV2 for Thanjavur, ACCESS-CM2 for Thirunelveli and ACCESS-CM2 for Thoothukudi respectively. This study emphasizes the importance of selecting an appropriate GCM. Selecting a suitable

关键词： CMIP6 Ranking Climate models compromise programming Future precipitation Performance evaluation

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Optimal collaborative demand-response planner for smart residential buildings

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ENERGY 2018年 161卷 370-380页

作者： Gomez-Herrera, Juan A. Anjos, Miguel F. Polytech Montreal GERAD CP 6079Succ Ctr Ville Montreal PQ H3C 3A7 Canada Polytech Montreal Dept Math & Ind Engn CP 6079Succ Ctr Ville Montreal PQ H3C 3A7 Canada

This work presents a collaborative scheme for the end-users in a smart building with multiple housing units. This approach determines a day-ahead operational plan that provides demand-response services by taking into account the amount of energy consumed per household, the use of shared storage and solar panels, and the amount of shifted load. We use a biobjective optimization model to trade off total user satisfaction versus total cost of energy consumption. The optimization works in combination with a price structure based on time and level of use that encourages load shifting and benefits the participants. Computational experiments and an extensive sensitivity analysis validate the performance of the proposed approach and help to clarify its strengths, its limits, and the requirements for ensuring the desired outcome. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Smart buildings Demand-response Residential load Biobjective optimization compromise programming

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A new normalized goal programming model for multi-objective problems: A case of supplier selection and order allocation

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2014年 148卷 158-165页

作者： Jadidi, O. Zolfaghari, S. Cavalieri, S. Bergamo Univ Dept Business Adm Bergamo BG Italy Ryerson Univ Dept Mech & Ind Engn Toronto ON M5B 2K3 Canada Univ Bergamo Dept Engn Dalmine BG Italy

This paper models the problem of supplier selection as a multi-objective optimization problem (MOOP) where minimization of price, rejects and lead-time are considered as three objectives. The paper considers two different cases: (1) the crisp MOOP in which the goals of objectives are predetermined;and (2) the fuzzy MOOP in which the weights of objectives are predetermined. In both cases, the aim is to achieve some levels of consistency among different objectives. To do so, a normalized goal programming approach is developed and tested for both cases. In order to compare the effectiveness of the proposed method, a comparative analysis is presented which includes weighted goal programming, compromise programming, TOPSIS, weighted objectives, min-max goal programming and weighted max-min models. An illustrative example reveals that our proposed model is able to achieve the desirable consistency among all objectives. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Multi-objective supplier selection Normalized goal programming compromise programming TOPSIS Weighted goal programming Min-max goal programming Weighted max-min model

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GuASPSO: a new approach to hold a better exploration-exploitation balance in PSO algorithm

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SOFT COMPUTING 2020年第7期24卷 4855-4875页

作者： Rezaei, Farshad Safavi, Hamid R. Isfahan Univ Technol Dept Civil Engn Esfahan Iran

This paper presents a new variant of particle swarm optimization (PSO) algorithm named guided adaptive search-based particle swarm optimizer (GuASPSO). In this algorithm, the personal best particles are all divided into a linearly decreasing number of clusters. Then, the unique global best guide of a given particle located at a cluster is obtained as the weighted average calculated over other clusters' best particles. Since the clustered particles are being well-distributed over the whole search space in the clustering process, there would be a moderate distance between each particle and its unique global best guide, contributing the particles neither to be trapped in local optima nor engaged in a drift leading to lose diversity in the search space. In this approach, the number of clusters is high at the early iterations and is gradually decreased by lapse of iterations to less stress the diversity factor and further stress the fitness role to cause the particles to better converge to the optimal point. Holding this balance between global and personal bests' role to attract the particles, on the one hand and between convergence and diversity, on the other hand, can hold a better exploration-exploitation balance in the proposed algorithm. To test the performance of GuASPSO, four popular meta-heuristic algorithms, including genetic algorithm, gravitational search algorithm, gray wolf optimizer, and PSO algorithm as well as 23 standard benchmark functions as the test beds, are employed. The experimental results validated GuASPSO as a robust well-designed algorithm to handle various optimization problems.

关键词： Particle swarm optimization Meta-heuristic algorithms Swarm-intelligence techniques Premature convergence compromise programming Self-organizing map (SOM)

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Replicability of Annual and Seasonal Precipitation by CMIP5 and CMIP6 GCMs over East Asia

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KSCE JOURNAL OF CIVIL ENGINEERING 2022年第4期26卷 1978-1989页

作者： Shiru, Mohammed Sanusi Shahid, Shamsuddin Chae, Seung-Taek Chung, Eun-Sung Seoul Natl Univ Sci & Technol Dept Civil Engn Seoul 01811 South Korea Fed Univ Dutse Fac Sci Dept Environm Sci Dutse 7156 Nigeria Univ Teknol Malaysia Dept Water & Environm Engn Johor Baharu 81310 Malaysia

global climate models (GCMs) structure is a source of uncertainty in climate change projections. Therefore, evaluation of the performances of GCMs is crucial for development of adaptation and mitigation measures and risk reduction against climate change impacts. This study quantified the performances of 10 GCMs of the Coupled Model Intercomparison Project 5 (CMIP5) and their CMIP6 equivalents in replicating precipitation over East Asia during 1975-2005. The CMIP5 and CMIP6 GCMs and their multi-model ensembles (MMEs) were annually and seasonally compared with the Global Precipitation Climatology Centre (GPCC) precipitation. compromise programming was used to rank GCMs by aggregating their scores obtained using statistical performance indices. Taylor diagram was used to assess their relative performances and GCMs' ability to replicate seasonal precipitation distribution was evaluated. Results revealed most CMIP6 GCMs' have better replicability of GPCC precipitation than CMIP5 GCMs. The MME mean of the CMIP6 showed better replicability of annual and seasonal GPCC precipitation than that of CMIP5. The CMIP6 MME also showed efficiency in simulating the seasonal precipitation distribution over East Asia. This study indicates improvements of some CMIP5 GCMs in their CMIP6 equivalents over East Asia. Findings from this study can be significant to policy makers and engineers in reducing the uncertainties in prediction of events such as floods and droughts.

关键词： compromise programming CMIP6 East Asia GCMs Statistical indices

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