Set Of Optimal Schemes Research Articles

A two-stage multi-objective optimization method for envelope and energy generation systems of primary and secondary school teaching buildings in China

A comfortable indoor environment plays an important role in improving students' learning efficiency and health. How to optimize the design of primary and secondary school education buildings to achieve a comfortable indoor environment, considering both energy and cost is a considerable challenge. This paper proposes a two-stage multi-objective optimization method based on a meta-model to obtain the optimal design scheme for primary and secondary school education buildings, based on daylighting, thermal comfort, energy savings and economy. The method has two stages: building envelope optimization and building generation system optimization. In the stage of building envelope optimization, an artificial neural network (ANN) model coupling optimization algorithm is used to optimize the building envelope. The performances of the non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO) algorithm are compared in the optimization process. In the stage of building generation system optimization, the design optimization of the building photovoltaic generation system is studied. Finally, the effectiveness of the two-stage optimization method is verified by a typical teaching building in Nanjing. The results show that the optimal scheme set of building envelope design can be obtained by this optimization method, and the optimal tilt angle and azimuth angle of the photovoltaic generation system are 30° and 210°, respectively. The minimum payback periods of the photovoltaic generation system are 11.75 years and 9.32 years under the policy of selling electricity that is not permitted and selling electricity that is permitted, respectively.

The determination of flood damage curve in areas lacking disaster data based on the optimization principle of variation coefficient and beta distribution

Flood loss assessment is an important part of urban flood risk management, and the establishment of disaster damage curve is the key of loss assessment. Because of the limitation of data, it is difficult for cities lacking disaster data to fit the damage curve through historical data. Generally, transferring the damage curve among regions is an effective method, but there are problems of data reference and statistical uncertainty. In view of the inland plain cities lacking disaster data, the damage factor of the data reference area can be transferred to the study area by referring to the principle of analogy. Then, based on the optimization principle of the minimum variation coefficient and the maximum beta distribution probability, the citation error and statistical error in the damage factor quotation were reduced, and the relatively accurate damage factor in the study area was obtained, and then the water depth - damage factor curve was established. Thus, a generalized damage curve fitting method for cities lacking disaster data was formed, which took the regional index values as the input parameters and the damage curves as the output results. Finally, taking Zhengzhou City, China as the study area, the loss curves of 10 property types were calculated. Compared with the original data, the average variation coefficient of the optimal scheme set was reduced by 0.1; the probability of the optimal value was increased by 1.39% compared with the average value. In addition, the method test was conducted in Jinan, China, where the data were available, and it was found that the three types of errors were significantly lower than the traditional comparison method of single city as reference object. This study is expected to provide a scientific reference for the establishment of flood damage curve in cities or areas lacking disaster data.

Engineering Water Pollution Control System Design Based on Robust Optimization Strategy

Environmental and health problems caused by engineering water pollution have become an important factor restricting the sustainable development of our country’s engineering. Our country’s engineering water pollution control has the characteristics of diverse structure, multiple objectives, related elements and great uncertainty, which brings challenges to the reasonable and effective development of engineering water pollution control planning. The structural design and technical selection method of engineering water pollution control established in this paper includes two parts: multi-objective robust optimization model and robust analysis framework. Among them, the multi-objective robust optimization model uses Latin hypercube sampling to improve the non-dominated sequencing genetic algorithm to provide an optimal scheme set that takes robustness into consideration for the planning of the engineering water pollution control system. A multi-attribute evaluation index system is constructed in the framework of robustness analysis. Through evaluation and selection of the optimal scheme set, subjectivity of system optimization scheme selection is reduced, and the scientific and quantitative level of scheme evaluation is improved. Based on the uncertainty analysis, key factors and sensitive areas affecting the robustness of the system are identified, which further improves the interpretation and application capabilities of the multi-objective robust optimization model.

Multiobjective Optimization Design and Performance Prediction of Centrifugal Pump Based on Orthogonal Test

In order to improve the hydraulic performance of the centrifugal pump, based on the original model, the optimization mathematical model with the four indexes head, efficiency, shaft power, and pump net positive suction head as objective function was established, and the multiobjective optimization design of the centrifugal pump was carried out by orthogonal test. Based on the L16(44) orthogonal table, 16 sets of orthogonal test schemes were made by selecting the four parameters impeller outlet width, blade inlet angle, blade outlet angle, and cape angle; the flow field numerical simulation was carried out by computational fluid dynamics technique; and the influence order of geometric parameters on optimization indexes was obtained by range analysis. The weight of each test factor on the optimization index was calculated by weight matrix, and a set of optimal schemes was obtained. Based on the external characteristic experimental bench of the IH 65‐60‐190 chemical centrifugal pump, the simulation values and test values of the prototype pump and the optimization pump were obtained under different working conditions. Under the rated flow, the head was reduced by 17.00%, the efficiency was increased by 9.14%, the shaft power was reduced by 21.50%, the pump net positive suction head was reduced by 16.69%, the curve hump was eliminated, the performance of centrifugal pump was improved, and the feasibility of the weight matrix optimization method was verified. The particle image velocimetry measurement system was used to measure the relative velocity of the internal media in the centrifugal pump. The results showed that the optimization pump had no obvious “jet‐wake” flow structure, its maximum velocity was less than the prototype pump, the area of low‐speed zone was larger than the prototype pump, the efficiency of the centrifugal pump was improved, and the shaft power and pump net positive suction head were reduced. The reason of the head decrease was analyzed from the internal flow situation, and the accuracy of the design optimization process was proved.

Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: The Portuguese case

A Multi-Criteria Decision Analysis (MCDA) tool was designed and used to support the evaluation of different electricity production scenarios. The MCDA tool is implemented in a user-friendly Excel worksheet and uses information obtained from a mixed integer optimization model, to produce a set of optimal schemes under different assumptions. Given the input, the MCDA allowed ranking different scenarios relying on their performance on 13 criteria covering economic, job market, quality of life of local populations, technical and environmental issues. The MCDA tool was used by a group of experts and academics with background in economics, engineering and environment. Regarding the totality of results, both the most and least expensive scenarios ranked first the same amount of times. These scenarios were, respectively, “Coal”, relying mainly in new coal power plants and “Maximum Renewable”, relying mainly in new wind and hydro power facilities. The opinions were divided towards these two solutions with different fundamental characteristics: “Maximum Renewable” with costs higher than “Coal” but leading to substantial reduction of the external energy dependency. Sensitivity analysis suggests that, although the costs are regarded as the most important criterion, those who had different rankings in their preferences have different attitudes towards other criteria.

Solution Method Of Optimal Scheme Set For Water Resources Scheduling Group Decision-Mahing Based On Multi-Agent Computation

Abstract Water resources allocation and scheduling management is a typical group decision-making problem. Detemvning how to realize the effective coordination between the decision makers, and how to generate the optimal solution set by computation are the keys to the research and development of water resources scheduling group decision support system. However, in the existing group decision support systems and literatures about water resources scheduling, the effective solution methods have not been reported. Firstly, this paper analyzes and designs amulti-Agent computation platform which can support the optimal scheme set, and build a functional structure model of multi-Agent computation platform. Then, it provides an algorithm of group decision making optimal scheme set based on Agent computation. The proposed algorithm generates the optimal scheme set by using the multi-Agent computation platform based on the genetic algorithm. Experimental results show that the proposed algorithm can make the coordina...