This paper presents an approach to generate optimal configurations for the neutron source distribution in subcritical systems. These optimal configurations are modeled as linear programming optimization problems (LPOP...
详细信息
This paper presents an approach to generate optimal configurations for the neutron source distribution in subcritical systems. These optimal configurations are modeled as linear programming optimization problems (LPOP), whose goal is to minimize the intensity of the neutron source distribution under constraints that define prescribed power density distribution in the subcritical system. The neutron source distribution simulates the neutrons released in spallation events in accelerator-driven subcritical reactors. Numerical results are given to illustrate that this approach can be used as an initial step of a computational tool to be used in the design of subcritical nuclear reactors. The supplementary computational tool aims at finding subcritical core configurations that can reduce the complexity of the high-energy particle accelerator.
We develop the fictitious play algorithm in the context of the linear programming approach for mean field games of optimal stopping and mean field games with regular control and absorption. This algorithm allows to ap...
详细信息
The use of EV batteries as secondary energy sources has recently been attracting great attention due to their large capacities. This paper is concerned with energy management of a workplace making use of the employees...
详细信息
ISBN:
(数字)9798350379051
ISBN:
(纸本)9798350379068
The use of EV batteries as secondary energy sources has recently been attracting great attention due to their large capacities. This paper is concerned with energy management of a workplace making use of the employees' EVs. We formulate such an energy management as a mixed-integer linear programming (MILP) problem by taking account of the arrival/departure status of the EVs and the benefits of the EV owners. Through a numerical simulation, we compare the effectiveness of the centralized algorithm and the distributed algorithm (Camisa et al. 2022) for finding a near-optimal solution to the MILP. The following points turn out from the simulation. If the number of EVs is small, the centralized algorithm can obtain a better solution to the MILP problem faster than the distributed algorithm without admitting the EV owners' decision-making. In contrast, in the case of a large number of EVs, the distributed algorithm can solve the problem faster than the centralized one taking account of the EV owners' decision-making at the price of the quality of its solution.
Integer linear programming (ILP) is an NP-complete combinatorial optimization problem (COP), suggesting that it is computationally challenging to solve due to its exponentially increased operations with scaling. As sh...
详细信息
ISBN:
(数字)9798350394061
ISBN:
(纸本)9798350394078
Integer linear programming (ILP) is an NP-complete combinatorial optimization problem (COP), suggesting that it is computationally challenging to solve due to its exponentially increased operations with scaling. As shown in Fig. 1, The ILP is relevant in various real-world scenarios such as computational biology [1], investment decision, automated driving, and electronic design automation [2]. An ILP solver aims to find a set of integer variables
$(x)$
to maximize a linear objective function
$(c\cdot x)$
, subject to a set of linear constraints
$(A\cdot x\leq b)$
. With the increasingly wide usage of ILP, various new solving algorithms [3] have been proposed, but the performance are limited by substantial memory access. ILP coefficients are fixed during solving, but software solvers on cache-register architectures frequently access cache to reload coefficients because of small register file size, causing up to a
$10^{14}\mathrm{x}$
disparity between stored and accessed memory bits. FPGA [4] and AISC [5] accelerated solvers improve the speed by customized processing element (PE), but they still need frequent accesses to Block-RAM or scratch pad. Compute-in-memory (CIM) solutions are well-suited for ILP solving which has extremely high data reuse, but existing CIM DNN accelerators incur precision loss with hardware tradeoffs, which is unacceptable for ILP where the feasibility checking must be correct. Previous all-digital CIM COP solver for Boolean variables [6] uses a customized
$6\mathrm{T}$
-6T{###}
$3\mathrm{T}$
cell, limiting their adaptability to different technologies.
This study utilizes a combination of linear programming analysis and Monte Carlo simulation to analyze the load characteristics of the electric vehicle-to-grid (V2G) system. The main focus is on evaluating the effecti...
详细信息
ISBN:
(数字)9798331516611
ISBN:
(纸本)9798331516628
This study utilizes a combination of linear programming analysis and Monte Carlo simulation to analyze the load characteristics of the electric vehicle-to-grid (V2G) system. The main focus is on evaluating the effectiveness of the V2G system in filling the grid load and regulating peak demand. Initially, a representative region is selected, and the grid load data for this region is presented without deploying the V2G system. Detailed analysis is conducted on the peaks and valleys in the load curves, providing a solid basis for comparison in the subsequent study. Subsequently, we constructed a mathematical model of the V2G system, which can accurately simulate the changes in the grid load data after introducing the V2G mechanism. Using this model, we thoroughly discussed how the V2G technology can intelligently regulate Evs' charging and discharging behaviors to manage the grid load effectively. It is worth noting that the grid load is affected by various complex and dynamically changing factors, and if these factors are ignored in the study, the resulting load optimization curves may be too idealized and lack the reference value for practical application. Therefore, this study innovatively introduces a “penalty term” mechanism to simulate the interference and fluctuation of other factors on the grid load except for the V2G system, so that the simulation results are closer to the real situation of grid operation. Ultimately, the results of this study clearly show that the load fluctuation of the power grid is significantly improved after the introduction of the V2G system. This finding not only verifies the great potential of V2G technology in improving the stability and flexibility of the power grid but also provides strong theoretical support and practical guidance for the further development of V2G technology and its wide application in smart grids in the future. In summary, this study not only deepens our understanding of the load characteristics of V2G systems b
This study proposes algorithms for optimal well placement in oil and gas fields. These algorithms allow the initial discrete programming problem of large dimensionality to be replaced by a series of linear programming...
详细信息
ISBN:
(数字)9798350375718
ISBN:
(纸本)9798350375725
This study proposes algorithms for optimal well placement in oil and gas fields. These algorithms allow the initial discrete programming problem of large dimensionality to be replaced by a series of linear programming problems of transportation type. In order to reduce the number of solved problems, it is proposed that random search algorithms be used.
This paper focuses on the research and application of linear optimization algorithm and grey Wolf optimization algorithm, takes the energy storage system configuration optimization of the park energy system as the res...
详细信息
ISBN:
(数字)9798331528676
ISBN:
(纸本)9798331528683
This paper focuses on the research and application of linear optimization algorithm and grey Wolf optimization algorithm, takes the energy storage system configuration optimization of the park energy system as the research object, and discusses in detail the similarities and differences and advantages of the energy storage system configuration under the three modes of independent operation, joint operation and collaborative configuration of wind storage. Firstly, a linear programming model for optimizing system configuration was established to determine the optimal energy storage power and capacity. In addition, under the consideration of State of Charge (SOC) and other constraints, the grey Wolf optimization algorithm was applied to further optimize the energy storage system configuration of independent parking lots to improve the accuracy and reliability of the optimization results. Secondly, the optimal energy storage configuration of the independent park is analyzed in detail, and the optimal energy storage scheme is deduced through the solution of the model and algorithm, which reflects the superiority of linear programming and grey Wolf optimization algorithm. The final focus is on developing a coordinated future configuration scheme for wind and solar storage. At the same time, the peak and valley electricity factor is introduced into the linear programming model, and the optimized grey Wolf algorithm is used to obtain the optimized energy scheduling and energy storage utilization strategy of the park's power generation and electricity price changes in the next five years.
This paper investigates the equivalence between a class of mixed-integer linear and linear programming prob-lems. By utilizing the addition of slack variables theorem, we demonstrate that certain optimization problems...
详细信息
ISBN:
(数字)9798350355284
ISBN:
(纸本)9798350355291
This paper investigates the equivalence between a class of mixed-integer linear and linear programming prob-lems. By utilizing the addition of slack variables theorem, we demonstrate that certain optimization problems arising in Model Predictive Control strategies, which involve logical constraints, can be solved as linear programming problems. Consequently, the equivalent linear programming problem can be solved using the standard and numerically efficient method named the Sim-plex method, as opposed to mixed-integer linear programming problems for which the best solution method is not clear. As a case study, we address the control problem of photovoltaic plants with energy storage systems. We design a model-based predictive control scheme based on our proposed equivalent linear programming problem to maximize economic benefits derived from energy delivered by both photovoltaic panels and energy storage systems to the grid in a deregulated electricity market, achieved by managing the charge and discharge of the energy storage. Additionally, the proposed scheme allows for the consideration of rate-based variable efficiency in the energy stor-age system model, offering a more comprehensive implementation compared to the previous approach in the literature, where only an ideal battery was considered. Furthermore, simulations reveal that the proposed control methodology reduces the execution time of model-predictive control iterations compared to another approach based on mixed-integer linear programming schemes with similar considerations, thereby enhancing the scalability of the solution.
The shift towards high-bandwidth networks driven by AI workloads in data centers and HPC clusters has unintentionally aggravated network latency, adversely affecting the performance of communication-intensive HPC appl...
详细信息
An (ε,δ)-DP mechanism is a mapping defined as follows. The domain of the mechanism is a finite set of objects, (also called the data points) such that a symmetric neighborhood relation over the data points is define...
详细信息
ISBN:
(数字)9798350387094
ISBN:
(纸本)9798350387100
An (ε,δ)-DP mechanism is a mapping defined as follows. The domain of the mechanism is a finite set of objects, (also called the data points) such that a symmetric neighborhood relation over the data points is defined. The range of the mechanism at each data point is a distribution over another set. Further more, neighboring data points must be mapped to two distributions that are not far away. The parametric notion of distance of two distribution in terms of the parameters (ε,δ) in the context of privacy theory, is first introduced by Dwork and her *** this paper, we study the following problem. Given a finite set $\mathcal{D}$ of data points, the neighboring relation, the parameters ε,δ, and a partial mechanism that is defined over a subset ${\mathcal{D}^\prime } \subseteq \mathcal{D}$, is there an extension of the mechanism defined over the entire set $\mathcal{D}$ that is identical to the partial mechanism on D
′
and also, is (ε,δ)-differential private. We show that there exists an algorithm to answer this question and it runs in time that is polynomial in the input variables. Our result generalizes a result of Medard et al. about optimum mechanism extension with respect to preferential query ordering.
暂无评论