The distributed ice load exerted on an engineering structure in a cold region can occasionally be treated as a static or dynamic problem. Examples of this are the thermal expansion load of the ice layer on a floating ...
详细信息
The distributed ice load exerted on an engineering structure in a cold region can occasionally be treated as a static or dynamic problem. Examples of this are the thermal expansion load of the ice layer on a floating nuclear power plant (FNPP), and the distributed ice pressure exerted on the bow of an icebreaker during a continuous ice breaking operation. However, such ice loads are difficult to measure directly. Accordingly, indirect ice load monitoring is an effective way to obtain the ice load with the input of structural monitoring data. The mathematical models used for ice load sensing are usually ill-posed, from which the accuracy and stability of the sensing results usually suffer. Although D-optimal design method (DOD), C-optimal design method (COD) and block C-optimal design method (BCOD) have been used to reduce the ill-posedness of a mathematical model, there are certain disadvantages in employing DOD, COD and BCOD methods. These methods mentioned above are prone to falling into local optima, resulting in local far-field monitoring and poor optimization performance, especially when the mathematical model dimensions are large. An improved simulated annealing algorithm (ISAA) was developed in this study to avoid local optima and described based on a specific case study-the sensing of ice load exerted on the reactor compartment section of a FNPP. Comparative analysis of ice load sensing results reveals that when the mathematical model has a large dimensionality, ISAA can yield much lower ill-posed mathematical models compared to the DOD, COD, and BCOD methods. The mathematical model optimized by ISAA exhibits higher robustness, leading to accurate sensing results.
The permutation flow shop scheduling problem (PFSP) is one of the most important and typical scheduling types in the mass customization production and is also a well-known NP-hard problem. However, most of the reporte...
详细信息
The permutation flow shop scheduling problem (PFSP) is one of the most important and typical scheduling types in the mass customization production and is also a well-known NP-hard problem. However, most of the reported algorithms lack the theoretical guidance to achieve the good accuracy and efficiency. To solve this problem, this paper proposes an efficient search method based on critical path with three theorems for the PFSP. Firstly, the concept of critical path and key points are defined according to the characteristics of the PFSP. On this basis, three theorems with the corresponding proofs are presented. Then, combined with above three theorems, a new neighborhood search method for the PFSP is developed. In each neighborhood search, only the first and last jobs in the processing sequence and the first job of each machine on the critical path need to be computed. No matter how large the scale of the problem is, this method only needs to search at most (2 m+2) times to find the optimal neighborhood solution (m is the number of machines). Finally, the new neighborhood search method is combined with an improved simulated annealing algorithm to solve the PFSP. To verify the performance of the proposed algorithm, this paper implement a set of comparative experiments with the-state-of-art methods on the part of the TA benchmark. By the proposed method, some significant improvements are obtained according to the experimental results. Meanwhile, under the same algorithm framework, the proposed method can reduce the 35.2% average computation time. Especially, the best-known upper bound of TA116 is updated from 26477 to 26469 by the proposed algorithm.
Resource sharing in a distributed environment can improve the utilization of resources. To promote the benign development of resource sharing behavior, a basic evaluation model of resource sharing is proposed, and an ...
详细信息
Resource sharing in a distributed environment can improve the utilization of resources. To promote the benign development of resource sharing behavior, a basic evaluation model of resource sharing is proposed, and an evaluation index system of distributed server resource sharing is constructed based on the model in this paper. The judgment matrices are constructed according to the analytic hierarchy process(AHP), and the simulatedannealingalgorithm(SAA) and the improved simulated annealing algorithm(ISAA) are respectively used to improve the consistency of each judgment matrix. The results show that the average consistency deviation of the judgment matrices optimized by ISAA is reduced 0.0421 and 0.0106 compared to EM and SAA respectively, and the convergence speed is about 77.8% higher than SAA. The standard deviations of the weight differences before and after optimization using ISAA and SAA are 0.0074 and 0.0259, respectively, so the weight fluctuations after ISAA optimization are relatively smaller. The weight distribution corresponding to each index is obtained when the consistencies of the judgment matrices are close to the optimal state, which provides a necessary technical foundation for the evaluation of distributed server resource sharing.
This paper studies the capacity of electric vehicle charging station (EVCS) and energy storage, and the optimization problem and model of electric vehicle (EV) charging scheduling plan. Based on the alternative energy...
详细信息
This paper studies the capacity of electric vehicle charging station (EVCS) and energy storage, and the optimization problem and model of electric vehicle (EV) charging scheduling plan. Based on the alternative energy storage effect of EVs, it is committed to improve the renewable energy consumption capacity in micro-grid, reduce the EVCS and energy storage capacity, and improve the comprehensive benefits of micro-grid investors. In this paper, considering the factors that affect the efficiency and system security, the determination model of EVCS and energy storage capacity is established, and the traditional simulatedannealingalgorithm (SA) is improved to create a disturbance mechanism for the optimization of charging scheduling plan, and the joint optimization is realized. The empirical analysis results show that the EVCS and energy storage capacity are reduced by about 50%, and the benefit of micro-grid investors is increased by about 7%. Therefore, this study can provide solutions for the planning of micro-grid with distributed energy, conventional users, energy storage and adjustable load, maximize renewable energy consumption and improve the satisfaction of all participants. (C) 2020 Elsevier Ltd. All rights reserved.
LNG importing strategies, in the literature, are primarily studied under a common single-factor framework. However, LNG importing strategies are affected by a variety of factors. To address this existing gap, this pap...
详细信息
LNG importing strategies, in the literature, are primarily studied under a common single-factor framework. However, LNG importing strategies are affected by a variety of factors. To address this existing gap, this paper proposes a Multi-Objective Programming model, which takes into account the cost, the country risk, the shipping risk, and the impact of extreme events. A pure structural change model is used to determine the risk impact coefficient for extreme events. An enhanced simulatedannealingalgorithm is then used to solve the LNG-importing optimization problem. An experimental study is further conducted to verify the practicability of the proposed approach in the case of China's LNG-importing data. The software implementation of the proposed model is developed in Python. The proposed model provides a decision support tool for LNG importing companies to find an efficient portfolio strategy for LNG importing. The optimization model can be used for analyzing similar scenarios involving such dimensions as economy, energy security, and especially energy diversification. (C) 2017 Elsevier Ltd. All rights reserved.
This paper studies the optimization of location-inventory-routing problem taking into account the retailers' requirement of delivery time. Based on the model of location-inventory-routing problem without time wind...
详细信息
This paper studies the optimization of location-inventory-routing problem taking into account the retailers' requirement of delivery time. Based on the model of location-inventory-routing problem without time window constraint, a model of location-inventory-routing problem with soft time window is built. Then an improved simulated annealing algorithm embedded tabu search is proposed to solve the model. Finally, a set of randomly generated computational experiments are conducted to evaluate the performance of our improvedalgorithm.
Using the randomness and stable tendency of a Y condition normal cloud generator, a cloud theory-based simulatedannealingalgorithm (CSA) is originally proposed, whose characteristic is approximately continuous decre...
详细信息
Using the randomness and stable tendency of a Y condition normal cloud generator, a cloud theory-based simulatedannealingalgorithm (CSA) is originally proposed, whose characteristic is approximately continuous decrease in temperature and implied "Backfire & Re-annealing". It fits the annealing process of solid matter in nature much better, overcomes the traditional simulatedannealingalgorithm (SA)'s disadvantages, which are slow searching speed and being trapped by local minimum easily, then enhances the veracity of final solution and reduces the time cost of the optimization process simultaneously. Theory analysis proves that CSA is convergent and typical function optimization experiments show that CSA is superior to SA in terms of convergence speed, searching ability and robustness. The result of the application using CSA for multiple observers sitting problem (MOST) in visibility-based terrain reasoning (VBTR) also declares the new algorithm's usefulness and effectiveness adequately. (C) 2009 Elsevier Ltd. All rights reserved.
Surface nuclear magnetic resonance is widely used for groundwater exploration and aquifer *** of surface nuclear magnetic resonance provides important information about aquifers,such as their depths,thickness and wate...
详细信息
Surface nuclear magnetic resonance is widely used for groundwater exploration and aquifer *** of surface nuclear magnetic resonance provides important information about aquifers,such as their depths,thickness and water *** this paper,we simply introduced the basic principles of nuclear magnetic resonance firstly,and then we discussed the relationship between surface nuclear magnetic resonance one dimensional kernel and pulse moment,medium conductivity,*** was found that surface nuclear magnetic resonance maximum depth is superimposed for one value of pulse moment and has smaller maximum depth in the higher conductive medium.A water content of layers lying below highly conductive layer is severely *** was also found that the condition number of one dimensional kernel matrix is small in the insulating *** improved simulated annealing algorithm from parameter restrictive condition,model disturbance,adaptive optimization method,circulate method,objective function,Markov chain and so ***,we inverted MRS data using singular value decomposition and improved simulated annealing algorithm. The experimental result of synthetic data shows inverting MRS data using SVD in insulating medium and improved simulated annealing algorithm are desirable.
暂无评论