In this paper, a penalty function method for multiobjective interval bilevel linear programming (MIBLP) problem is proposed. Firstly, interval order relation is used to transform objective functions. The possibility l...
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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...
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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.
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...
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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.
In the pursuit of a sustainable energy future, optimizing the sale prices of renewable energy sources is crucial for maximizing their economic viability. This research paper presents a linear programming (LP) approach...
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ISBN:
(数字)9798331542559
ISBN:
(纸本)9798331542566
In the pursuit of a sustainable energy future, optimizing the sale prices of renewable energy sources is crucial for maximizing their economic viability. This research paper presents a linear programming (LP) approach to determine the optimal sale prices for wind and solar energy. The study utilizes LP techniques to model and solve for the optimal pricing strategy that balances production capacity and market conditions. Our findings reveal that the optimal sale price for wind energy is $0.04 per kWh when production reaches 1000 kWh, while for solar energy, the optimal sale price is the same at a production level of 500 kWh. The LP model effectively accounts for variations in energy production and market demand, providing a strategic framework for setting competitive sale prices. This approach enhances profitability for renewable energy producers and supports more efficient integration of renewable sources into the energy market. The results underscore the potential of LP techniques in refining pricing strategies and contribute to the broader goal of advancing sustainable energy solutions. This research provides actionable insights for policymakers and energy producers seeking to optimize renewable energy pricing in dynamic market environments.
This paper proposes two approaches for reducing the impact of the error floor phenomenon when decoding quantum low-density parity-check codes with belief propagation based algorithms. First, a low-complexity syndrome-...
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ISBN:
(数字)9781728190549
ISBN:
(纸本)9781728190556
This paper proposes two approaches for reducing the impact of the error floor phenomenon when decoding quantum low-density parity-check codes with belief propagation based algorithms. First, a low-complexity syndrome-based linear programming (SB- LP) decoding algorithm is proposed, and second, the proposed SB-LP is applied as a post-processing step after syndrome-based min-sum (SB-MS) decoding. For the latter case, a new early stopping criterion is introduced to decide when to activate the SB- LP algorithm, avoiding executing a predefined maximum number of iterations for the SB-MS decoder. Simulation results show, for a sample hypergraph code, that the proposed decoder can lower the error floor by two to three orders of magnitude compared to SB-MS for the same total number of decoding iterations.
To meet stringent performance requirements, communication networks are becoming increasingly programmable and flexible, supporting fast and frequent adjustments. However, reconfiguring networks in a dependable and tra...
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ISBN:
(数字)9798350383508
ISBN:
(纸本)9798350383515
To meet stringent performance requirements, communication networks are becoming increasingly programmable and flexible, supporting fast and frequent adjustments. However, reconfiguring networks in a dependable and transiently consistent manner is known to be algorithmically challenging. This paper revisits the fundamental problem of how to update the routes in a network in a (transiently) loop-free manner, considering both the Strong Loop-Freedom (SLF) and the Relaxed Loop-Freedom (RLF) *** present two fast algorithms to solve the SLF and RLF problem variants exactly, to optimality. Our algorithms are based on a parameterized integer linear program which would be intractable to solve directly by a classic solver. Our main technical contribution is a lazy cycle breaking strategy which, by adding constraints lazily, improves performance dramatically, and outperforms the state-of-the-art exact algorithms by an order of magnitude on realistic medium-sized networks. We further explore approximate algorithms and show that while a relaxation approach is relatively slow, with a local search approach short update schedules can be found, outperforming the state-of-the-art *** the theoretical front, we also provide an approximation lower bound for the update time of the state-of-the-art algorithm in the literature. As a contribution to the research community, we made all our code and implementations publicly available.
This paper investigates the state-feedback and observer-based feedback control for positive cyber-physical systems. A novel positive anti-attack controller is first proposed for the systems by introducing a switched c...
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ISBN:
(数字)9798350380286
ISBN:
(纸本)9798350380293
This paper investigates the state-feedback and observer-based feedback control for positive cyber-physical systems. A novel positive anti-attack controller is first proposed for the systems by introducing a switched control strategy. By developing observer technique for cyber-physical systems, a positive controller equipped with dynamic output-feedback approach is refined to estimate unavailable output. Under the designed controllers, the positive and stable with $L_{1}$-gain performance are reached. Then, a matrix decomposition method is employed to design observer and controller gains. All presented conditions are described via linear programming. Finally, an illustrative example is given to verify the effectiveness of the proposed design.
The article presents a new method of linear programming, called the surface movement method. This method constructs an optimal objective path on the surface of the feasible polytope from the initial boundary point to ...
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linear programming is a widely applicable mathematical operation method. In this paper, two solutions of linear programming and state parameter extraction can be used to simplify the inequality group and transfer the ...
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linear programming is a widely applicable mathematical operation method. In this paper, two solutions of linear programming and state parameter extraction can be used to simplify the inequality group and transfer the high-dimensional state utility function in football. This can speed up the generation of joint strategies for football teams in the game. This paper uses the free-kick technical football cooperation as an example to conduct an empirical study on the linear programming method of state parameters. In this paper, combined with the traditional motion information modeling method, a free ball path planning based on the linear programming gradient method is established. At the same time, this paper adopts an asymptotic method based on linear programming to solve the trajectory of any football. Finally, an experimental study on the linear programming gradient method for state feature vectorization is carried out. Experiments verify the effectiveness of this method. The mathematical model accurately predicts the linear programming of football training.
We derive a linear programming bound on the maximum cardinality of error-correcting codes in the sum-rank metric. Based on computational experiments on relatively small instances, we observe that the obtained bounds o...
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