Optimization under Uncertainty Optimization under Uncertainty: An Overview Urmila Diwekar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Two-Stage Stochastic Linear Programming: A Tutorial Vicente Rico-Ramirez . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Combinatorial Optimization under Uncertainty Ki-Joo Kim . . . . . . . . . . . . . . . . . . . . . . . . . . ...

in the process of milk production, the highest cost relates to animal feed. based on reports provided by the experts, around seventy percent of dairy livestock costs included feed costs. in order to minimize the total price of livestock feed, according to the limits of feed sources in each region or season, and also the transportation and maintenance costs and ultimately milk price reduction, o...

Currently, most of the piezoelectric structures are designed under deterministic conditions, where influence uncertain factors on output motion accuracy is ignored. In this work, a probabilistic reliability-based topology optimization method for structure proposed to deal with working voltage uncertainty. A nested double-loop algorithm minimizing total volume while satisfying reliability requir...

Structural analysis and design optimization have recently been extended to the stochastic approach to consider various uncertainties. However, in areas where it is not possible to produce accurate statistical information for input data, the probabilistic method is not appropriate for stochastic structural analysis and design optimization, because improper modeling of uncertainty could cause a g...

in this paper, we consider a multi-site production planning problem subject to uncertainty in demand and workforce expenses. in our new mathematical model, we presented a production planning system considering failure in rework and breakdown. we also survey human workforce allocation and its expenses which are considered uncertain due to some tradeoff between company’s benefits and workforce :u...

Model-based multi-objective optimization is a useful tool to compute optimal trade-offs between multiple conflicting objectives such as minimizing energy consumption while maximizing productivity. However, the computational cost of solving problems high. In addition, model approximates real process, meaning uncertainty inherently present. To avoid erroneous predictions process performance and u...

rainfall-runoff modeling is most important component in the water resource management of river basins. the successful application of a conceptual rainfall-runoff model depends on how well it is calibrated. the degree of difficulty in solving the global optimization method is generally dependent on the dimensionality of the model and certain of the characteristics of object function. the purpose...

This paper introduces a methodology for considering the uncertainties in stability analysis of gravity dams. For this purpose, a conceptual model based on the fuzzy set theory and Genetic Algorithm (GA) optimization is developed to be coupled to a gravity dam analysis model. The uncertainties are represented by the fuzzy numbers and the GA is used to estimate in what...