In sponsored search advertising (SSA), advertisers need to select keywords and determine matching types for selected keywords simultaneously, i.e., keyword targeting. An optimal keyword targeting strategy guarantees r...
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CONTEXTFarm management occurs against a backdrop of weather-year variation. How important is it for farming system models to capture this variation and the management tactics matched to that variation?OBJECTIVEThis st...
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<正>Product recovery has received increasing atten- tions in the past *** of the existing models on the subject are ***,randomness is one of the characteristics of product recovery ***- ing this situation,this paper...
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<正>Product recovery has received increasing atten- tions in the past *** of the existing models on the subject are ***,randomness is one of the characteristics of product recovery ***- ing this situation,this paper proposes a generalized product recovery network with stochastic quantities of returned prod- ucts and stochastic transportation *** on different decision-making criteria,three stochastic programming mod- els are formulated to characterize this problem.
While online social networks (OSNs) have become an important platform for information exchange, the abuse of OSNs to spread misinformation has become a significant threat to our society. To restrain the propagation of...
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ISBN:
(纸本)9781538660522
While online social networks (OSNs) have become an important platform for information exchange, the abuse of OSNs to spread misinformation has become a significant threat to our society. To restrain the propagation of misinformation in its early stages, we study the Distance-constrained Misinformation Combat under Uncertainty problem, which aims to both reduce the spread of misinformation and enhance the spread of correct information within a given propagation distance. The problem formulation considers the competitive diffusion of misinformation and correct information. It also accounts for the uncertainty in identifying initial misinformation adopters. For competitive propagation with major-threshold activation, we propose a solution based on stochastic programming and provide an upper-bound in the presence of uncertainty. We propose an efficient Combat Seed Selection algorithm to tackle general-threshold activation, in which we define a measure, “effectiveness”, to evaluate the contribution of nodes to the fight against misinformation. Through extensive experiments, we validate that our algorithm outputs high-quality solution with very fast computation.
A rational behavior of a consumer is analyzed when the user participates in a Peak Time Rebate (PTR) mechanism, which is a demand response (DR) incentive program based on a baseline. A multi-stage stochastic programmi...
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Convex sample approximations of chance-constrained optimization problems are considered, in which chance constraints are replaced by sets of sampled constraints. We propose a randomized sample selection strategy that ...
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Demand response has been implemented by distribution system operators to reduce peak demand and mitigate contingency issues on distribution lines and substations. Specifically, the campus-based commercial buildings ma...
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stochastic programming is widely used for energy system design optimization under uncertainty but can exponentially increase the computational complexity with the number of scenarios. Common scenario reduction techniq...
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Wind power generation brings new challenges to power system scheduling due to the uncertainty caused by its imprecise prediction. Especially when multiple wind farms are taken into consideration, models and optimizati...
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ISBN:
(纸本)9781467327275
Wind power generation brings new challenges to power system scheduling due to the uncertainty caused by its imprecise prediction. Especially when multiple wind farms are taken into consideration, models and optimization methods which are good at dealing with deterministic scheduling problems do not work. stochastic programming (SP) has been usually applied to solve the problem with wind power uncertainty, which has many advantages and limitations. A new concept of Robust Scheduling (RS) is first proposed in this paper and the mathematical model is established. The Mixed Integer programming (MIP) is adopted for solving the model. The paper also defines the extreme scenarios set for description of wind power uncertainty. By using it we can achieve robust schedule by avoiding the use of the probabilistic distribution of wind power, which is often hard to acquire. Case study based on the modified IEEE118 bus system proves that the RS model and optimization method are effective and can acquire a robust schedule over wind power uncertainty.
stochastic programming models can lead to very large-scale optimization problems for which it may be impossible to enumerate all possible scenarios. In such cases, one adopts a sampling-based solution methodology in w...
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