Results 11 to 20 of about 99,030 (308)
IEEE Access, 2021 Simultaneous deployment of the electric vehicle charging stations (EVCSs) and distributed photovoltaic stations (DPVSs) in the distribution systems is an effective way to reduce greenhouse gas emissions, promote renewable power adoption, and achieve ...
Xinsong Zhang +4 more
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Distributionally Robust Chance Constrained Programming with Generative Adversarial Networks (GANs) [PDF]
AIChE Journal, 2020 This paper presents a novel deep learning based data-driven optimization method. A novel generative adversarial network (GAN) based data-driven distributionally robust chance constrained programming framework is proposed.
Shipu Zhao, F. You
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A chance-constrained stochastic approach to intermodal container routing problems. [PDF]
PLoS ONE, 2018 We consider a container routing problem with stochastic time variables in a sea-rail intermodal transportation system. The problem is formulated as a binary integer chance-constrained programming model including stochastic travel times and stochastic ...
Yi Zhao +3 more
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Diameter Constrained Fuzzy Minimum Spanning Tree Problem [PDF]
International Journal of Computational Intelligence Systems, 2013 In this paper, we have studied the constrained version of the fuzzy minimum spanning tree problem. Costs of all the edges are considered as fuzzy numbers.
Sk. Md. Abu Nayeem, Madhumangal Pal
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IEEE Access, 2021 The active distribution network management (ADNM) equipped by active distribution networks (ADNs) can enhance the resilience of the network after failure.
Guanghe Wang +6 more
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Output‐feedback stochastic model predictive control of chance‐constrained nonlinear systems
IET Control Theory & Applications, 2023 This study covers the output‐feedback model predictive control (MPC) of nonlinear systems subjected to stochastic disturbances and state chance constraints. The stochastic optimal control problem is solved in a stochastic dynamic programming fashion, and
Jingyu Zhang, Toshiyuki Ohtsuka
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A Synthesizing Effect-Based Solution Method for Stochastic Rough Multi-objective Programming Problems [PDF]
International Journal of Computational Intelligence Systems, 2014 Multi-objective programming with uncertain information has been widely applied in modeling of industrial produce and logistic distribution problems. Usually the expectation value model and chance-constrained model as solution models are used to deal with
Lei Zhou, Guoshan Zhang, Fachao Li
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Future Business Journal, 2018 Linear Programming model is an important tool used to solve constrained optimization problems. In fact, the real life problems are usually occurring in the presence of uncertainty.
Maha Ismail +2 more
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FEM shakedown analysis of structures under random strength with chance constrained programming
Vietnam Journal of Mechanics, 2022 Direct methods, comprising limit and shakedown analysis, are a branch of computational mechanics. They play a significant role in mechanical and civil engineering design.
Ngoc Trinh Tran +6 more
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