Horsetail matching: a flexible approach to optimization under uncertainty
نویسندگان
چکیده
منابع مشابه
Horsetail Matching for Optimization Under Probabilistic, Interval and Mixed Uncertainties
The importance of including uncertainties in the design process of aerospace systems is becoming increasingly recognized, leading to the recent development of many techniques for optimization under uncertainty. Most existing methods represent uncertainties in the problem probabilistically; however, in many real life design applications it is often difficult to assign probability distributions t...
متن کاملStochastic programming approach to optimization under uncertainty
In this paper we discuss computational complexity and risk averse approaches to two and multistage stochastic programming problems. We argue that two stage (say linear) stochastic programming problems can be solved with a reasonable accuracy by Monte Carlo sampling techniques while there are indications that complexity of multistage programs grows fast with increase of the number of stages. We ...
متن کاملA Novel Sampling Approach to Combinatorial Optimization Under Uncertainty
The generalized approach to stochastic optimization involves two computationally intensive recursive loops: (1) the outer optimization loop, (2) the inner sampling loop. Furthermore, inclusion of discrete decision variables adds to the complexity. The focus of the current endeavor is to reduce the computational intensity of the two recursive loops. The study achieves the goals through an improv...
متن کاملExtending Horsetail Matching for Optimization Under Probabilistic, Interval and Mixed Uncertainties
This paper presents a new approach for optimization under uncertainty in the presence of probabilistic, interval and mixed uncertainties, avoiding the need to specify probability distributions on uncertain parameters when such information is not readily available. Existing approaches for optimization under these types of uncertainty mostly rely on treating combinations of statistical moments as...
متن کاملA scenario based approach for flexible resource loading under uncertainty
Order acceptance decisions in manufacture-to-order environments are often made based on incomplete or uncertain information. To promise reliable due dates and to manage resource capacity adequately, resource capacity loading is an indispensable supporting tool. We propose a scenario based approach for resource loading under uncertainty that minimises the expected costs. The approach uses an MIL...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Engineering Optimization
سال: 2017
ISSN: 0305-215X,1029-0273
DOI: 10.1080/0305215x.2017.1327581