scholarly journals Building Thermo-Modernisation Solution Based on the Multi-Objective Optimisation Method

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1433 ◽  
Author(s):  
Małgorzata Basińska ◽  
Dobrosława Kaczorek ◽  
Halina Koczyk
Keyword(s):  
Natural Ventilation ◽  
Evaluation Criteria ◽  
Optimal Solution ◽  
Primary Energy ◽  
Energy Ratio ◽  
Additional Energy ◽  
Multi Objective ◽  
Weighted Sum Method ◽  
Global Cost ◽  
Alternative Solutions

This study presents a multi-objective optimisation of building thermo-modernisation for multi-family buildings. The applied model has considered alternative solutions for insulation materials, with different thicknesses and different types of windows. The weighted sum method was applied to find a solution considering the minimisation of global cost, primary energy ratio and CO2 emissions. The solutions were compared for a building equipped with natural ventilation, and with mechanical supply—exhaust ventilation. In reference to the two considered types of ventilation, we analysed how the modification of an insulation thickness, its type and the type of installed windows, can be converted into individual evaluation criteria. The weights of the considered criteria were changed; however, this had no influence on the optimal solution. If the aim is to achieve the standards of zero-energy buildings, natural ventilation cannot be applied, despite the high value of thermal insulation of the building envelopes. Alternative solutions exist for buildings with natural ventilation and mechanical ventilation with heat recovery, where the primary energy ratio is the same for both, but the global costs are different. The additional energy and environmental input for the production of materials and elements to be replaced are insignificant in comparison to the savings brought about by thermo-modernisation.

scholarly journals The use of multi-criteria optimization to choose solutions for energy-efficient buildings

2017 ◽  
Vol 65 (6) ◽  
pp. 815-826 ◽  
Author(s):  
M. Basińska
Keyword(s):  
Energy Demand ◽  
Residential Buildings ◽  
Optimal Solution ◽  
Primary Energy ◽  
Building Envelope ◽  
Technical Equipment ◽  
Energy Index ◽  
Global Cost ◽  
Technical Solutions ◽  
Installation Technology

AbstractThe goal of this paper was to optimize the building envelope and technical equipment in the building through the mitigation of the global cost value, and then to evaluate the influence of the chosen assumptions on the primary energy index. The analyses carried out using global cost method allow for finding the cost optimal solution but only for the some range of primary energy index variability. In order to find the optimal solutions it was proposed to use the multi-criteria optimisation, assuming the following as basic criteria: a global cost value and investment prices increase (economic criteria), a primary energy index (energy-related criterion), an emission of carbon dioxide (environmental criterion). The analysed case study refers to the technical solutions for the residential buildings with the usable energy demand at the level of 40 and 15 kWh/m2/a. The presented method might be applied to different types of buildings: those being designed and those being the subject of the thermo-modernisation. The results demonstrate that the proposed model allows for classification of the alternative technical solutions regarding the designing process and the building’s technical equipment. The carried out analyses indicate the economic possibility to achieve the low energy building standard and show the need to concentrate the activities related to the installation technology and used energy source.

scholarly journals Multi-Objective Restricted Solid Transportation Problem in Intuitionistic Fuzzy Environment with Emission Cost

2019 ◽  
Vol 8 (2S3) ◽  
pp. 722-727 ◽  
Keyword(s):  
Transportation Problem ◽  
International Energy Agency ◽  
Optimal Solution ◽  
Transport Sector ◽  
Solid Transportation Problem ◽  
Energy Agency ◽  
Multi Objective ◽  
Intuitionistic Fuzzy ◽  
Weighted Sum Method ◽  
Fuzzy Environment

Transportation plays key role in logistic and supply chain management for decreasing cost and enhances service. The transport sector contributes 23% of the total CO2 emissions in the world according to the latest estimates of the International Energy Agency (IEA).There is a direct link between weight of the quantity transported and co2 emission for the freight transport. This paper presents multi objective restricted solid transportation problem in intuitionistic fuzzy ambiance with emission cost which is based on weight of the quantity transported and vehicle cost under some restriction on transported amount. An extra constraint on the total budget at each destination is imposed. Transportation models are formulated under crisp and fuzzy environments and fuzzy models are converted into crisp using average method. The total time and emission cost based on weight of the quantity transported for restricted and unrestricted models are compared. The optimal solution is obtained by using weighted sum method and Lingo 13.0 Software. Mathematical example is given to validate the proposed mode

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

A two-sided matching decision-making approach based on regret theory under intuitionistic fuzzy environment

2021 ◽  
pp. 1-18
Author(s):  
Xiang Jia ◽  
Xinfan Wang ◽  
Yuanfang Zhu ◽  
Lang Zhou ◽  
Huan Zhou
Keyword(s):  
Decision Making ◽  
Hamming Distance ◽  
Optimal Solution ◽  
Intuitionistic Fuzzy Sets ◽  
Regret Theory ◽  
Multi Objective ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Objective Model ◽  
Single Objective

This study proposes a two-sided matching decision-making (TSMDM) approach by combining the regret theory under the intuitionistic fuzzy environment. At first, according to the Hamming distance of intuitionistic fuzzy sets and regret theory, superior and inferior flows are defined to describe the comparative preference of subjects. Hereafter, the satisfaction degrees are obtained by integrating the superior and inferior flows of the subjects. The comprehensive satisfaction degrees are calculated by aggregating the satisfaction degrees, based on which, a multi-objective TSMDM model is built. Furthermore, the multi-objective TSMDM model is converted to a single-objective model, the optimal solution of the latter is derived. Finally, an illustrative example and several analyses are provided to verify the feasibility and the effectiveness of the proposed approach.

A fuzzy multi-objective programming optimization model for emergency resource dispatching under equitable distribution principle

2021 ◽  
pp. 1-10
Author(s):  
Zhaoping Tang ◽  
Wenda Li ◽  
Shijun Yu ◽  
Jianping Sun
Keyword(s):  
Optimization Model ◽  
Programming Model ◽  
Ideal Point ◽  
Optimal Solution ◽  
Multi Objective ◽  
Emergency Rescue ◽  
Satisfaction Degree ◽  
Multi Objective Programming ◽  
Parameter Interval ◽  
Objective Programming

In the initial stage of emergency rescue for major railway emergencies, there may be insufficient emergency resources. In order to ensure that all the emergency demand points can be effectively and fairly rescued, considering the fuzzy properties of the parameters, such as the resource demand quantity, the dispatching time and the satisfaction degree, the railway emergency resources dispatching optimization model is studied, with multi- demand point, multi-depot, and multi-resource. Based on railway rescue features, it was proposed that the couple number of relief point - emergency point is the key to affect railway rescue cost and efficiency. Under the premise of the maximum satisfaction degree of quantity demanded at all emergency points, a multi-objective programming model is established by maximizing the satisfaction degree of dispatching time and the satisfaction degree of the couple number of relief point - emergency point. Combined with the ideal point method, a restrictive parameter interval method for optimal solution was designed, which can realize the quick seek of Pareto optimal solution. Furthermore, an example is given to verify the feasibility and effectiveness of the method.

OPTIMAL PREDICTION AND DESIGN OF SURFACE ROUGHNESS FOR CNC TURNING OF AL7075-T6 BY USING THE TAGUCHI HYBRID QPSO ALGORITHM

2016 ◽  
Vol 40 (5) ◽  
pp. 883-895 ◽  
Author(s):  
Wen-Jong Chen ◽  
Chuan-Kuei Huang ◽  
Qi-Zheng Yang ◽  
Yin-Liang Yang
Keyword(s):  
Surface Roughness ◽  
Particle Swarm Optimization ◽  
Predictive Models ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Cutting Parameters ◽  
Optimization Methods ◽  
Swarm Optimization ◽  
Cnc Turning ◽  
Multi Objective

This paper combines the Taguchi-based response surface methodology (RSM) with a multi-objective hybrid quantum-behaved particle swarm optimization (MOHQPSO) to predict the optimal surface roughness of Al7075-T6 workpiece through a CNC turning machining. First, the Taguchi orthogonal array L27 (36) was applied to determine the crucial cutting parameters: feed rate, tool relief angle, and cutting depth. Subsequently, the RSM was used to construct the predictive models of surface roughness (Ra, Rmax, and Rz). Finally, the MOHQPSO with mutation was used to determine the optimal roughness and cutting conditions. The results show that, compared with the non-optimization, Taguchi and classical multi-objective particle swarm optimization methods (MOPSO), the roughness Ra using MOHQPSO along the Pareto optimal solution are improved by 68.24, 59.31 and 33.80%, respectively. This reveals that the predictive models established can improve the machining quality in CNC turning of Al7075-T6.

Multi-Objective Trajectory Optimization of Free-Floating Space Manipulator Using NSGA-II

2015 ◽  
Vol 713-715 ◽  
pp. 800-804 ◽  
Author(s):  
Gang Chen ◽  
Cong Wei ◽  
Qing Xuan Jia ◽  
Han Xu Sun ◽  
Bo Yang Yu
Keyword(s):  
Trajectory Optimization ◽  
Interpolation Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Joint Space ◽  
Motion Path ◽  
Objective Functions ◽  
Nsga Ii ◽  
Space Manipulator ◽  
Multi Objective

In this paper, a kind of multi-objective trajectory optimization method based on non-dominated sorting genetic algorithm II (NSGA-II) is proposed for free-floating space manipulator. The aim is to optimize the motion path of the space manipulator with joint angle constraints and joint velocity constraints. Firstly, the kinematics and dynamics model are built. Secondly, the 3-5-3 piecewise polynomial is selected as interpolation method for trajectory planning of joint space. Thirdly, three objective functions are established to simultaneously minimize execution time, energy consumption and jerk of the joints. At last, the objective functions are combined with the NSGA-II algorithm to get the Pareto optimal solution set. The effectiveness of the mentioned method is verified by simulations.

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