In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...

water shortage crisis is an issue that has led to drastic changes in different agricultural policies, especially in arid and semi-arid areas. uncertainty in the amount of resources, e.g. water, used for agricultural production entails risk for farmers' income and cropping pattern changes. in the present study, the robust optimization model was used for optimal allocation of arable lands of khor...

We consider the problem of preference-based search for configurable products. We focus on example-based tools that interactively show both candidates (best options given current preferences) and suggestions to stimulate preference expression. Suggestions are generated to maximize the chance of eliciting further preferences using our lookahead principle. We present Probabilistic Constraint Optim...

We consider the problem of preference-based search for configurable products. We focus on example-based tools that interactively show both candidates (best options given current preferences) and suggestions to stimulate preference expression. Suggestions are generated to maximize the chance of eliciting further preferences using our lookahead principle. We present Probabilistic Constraint Optim...

Virtual power plant (VPP) can be studied to investigate how energy is purchased or sold in the presence of electricity market price uncertainty. The VPP uses different intermittent distributed sources such as wind turbine, flexible loads, and locational marginal prices (LMPs) in order to obtain profit. VPP should propose bidding/offering curves to buy/sell from/to day-ahead market. In this pape...

1. Abstract In practical engineering applications, there exist two different types of uncertainties: aleatory and epistemic uncertainties. Aleatory uncertainty is classified as objective and irreducible uncertainty with sufficient information on input uncertainty data, whereas epistemic uncertainty is a subjective and reducible uncertainty that stems from lack of knowledge on input uncertainty ...

Co-firing biomass plants are of extensive demand due to utilization of both agricultural residues (main) and natural gas (stand-by). Researchers have shown that one strategic decision in establishment of agricultural residues based plants, is location optimization problem. Moreover, mismatch between agricultural lands and biomass plants can lead to high transportation costs and related carbon d...

in this paper, we introduce a model  to optimization of milk run system that is one of vrp problem with time window and uncertainty in inventory. this approach led to the routes with minimum cost of transportation while satisfying all inventory in a given bounded set of uncertainty .the problem is formulated as a robust optimization problem. since the resulted problem illustrates that grows up ...

optimization of maintenance resources to maximize the system availability is a major concern in different manufacturing systems. therefore, a lot of effort is put to construct optimization models to reach the maximum availability level and to reduce the costs of lack of availability. however, despite these efforts, data uncertainty in the real world problems was neglected in proposed models whi...