Zobrazeno 1 - 10
of 113
pro vyhledávání: '"William B. Haskell"'
Autor:
Ian N. Higginson
Publikováno v:
Polar Record. 35:164-165
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f0d0b96b0eb66b02ee3bdb759dc619c
https://doi.org/10.1017/s0032247400026590
https://doi.org/10.1017/s0032247400026590
Publikováno v:
SIAM Journal on Optimization. 32:1446-1470
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aebe2e28258695baa766906d22ca45ae
https://doi.org/10.1137/20m1316524
https://doi.org/10.1137/20m1316524
Publikováno v:
IISE Transactions. 55:187-200
This paper studies a model for risk aversion when designing a flexible capacity expansion plan for a multi-facility system. In this setting, the decision maker can dynamically expand the capacity of each facility given observations of uncertain deman
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70cd8e038a4a5121d077c60a75fabe87
https://doi.org/10.1080/24725854.2021.2022815
https://doi.org/10.1080/24725854.2021.2022815
Publikováno v:
INFORMS Journal on Computing. 34:569-585
A quantile is a popular performance measure for a stochastic system to evaluate its variability and risk. To reduce the risk, selecting the actions that minimize the tail quantiles of some loss distributions is typically of interest for decision make
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ceaceefce579f732280172df53e7077f
https://doi.org/10.1287/ijoc.2020.1049
https://doi.org/10.1287/ijoc.2020.1049
Publikováno v:
Applied Mathematics & Optimization. 84:805-835
This paper studies constrained information projections on Banach spaces with respect to a Gaussian reference measure. Specifically our interest lies in characterizing projections of the reference measure, with respect to the KL-divergence, onto sets
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::283f5fb491b19154b3d3938f22d22254
https://doi.org/10.1007/s00245-021-09786-4
https://doi.org/10.1007/s00245-021-09786-4
Publikováno v:
Annals of Operations Research. 295:809-841
The CoMirror algorithm, by Beck et al. (Oper Res Lett 38(6):493–498, 2010), is designed to solve convex optimization problems with one functional constraint. At each iteration, it performs a mirror-descent update using either the subgradient of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a82cb93d7a511b1d10965ff0c36fae54
https://doi.org/10.1007/s10479-020-03766-7
https://doi.org/10.1007/s10479-020-03766-7
Publikováno v:
IEEE Transactions on Automatic Control. 65:115-129
We propose universal randomized function approximation-based empirical value learning (EVL) algorithms for Markov decision processes. The “empirical” nature comes from each iteration being done empirically from samples available from simulations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::249b766b8f3321d61dfcfaa239e241d3
https://doi.org/10.1109/tac.2019.2907414
https://doi.org/10.1109/tac.2019.2907414
Publikováno v:
Mathematical Methods of Operations Research. 91:501-544
This paper considers an inexact primal-dual algorithm for semi-infinite programming (SIP) for which it provides general error bounds. We create a new prox function for nonnegative measures for the dual update, and it turns out to be a generalization
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0553b0ff885ff2ad1d0d5259660d8c3
https://doi.org/10.1007/s00186-019-00698-2
https://doi.org/10.1007/s00186-019-00698-2
Publikováno v:
The International Journal of Life Cycle Assessment. 25:443-455
Life cycle assessment (LCA) is commonly used to analyze the environmental profile of a material and product. For example, the selection of building insulation is crucial to ensure that energy and financial conservation goals can be met. Most of the c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71bd3ba9ef3c4a28ffe99419721c407c
https://doi.org/10.1007/s11367-019-01711-w
https://doi.org/10.1007/s11367-019-01711-w
Publikováno v:
Optimization. 68:2397-2426
The distributionally robust Markov Decision Process (MDP) approach asks for a distributionally robust strategy that achieves the maximal expected total reward under the most adversarial distributio...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e6fcb50c46b8d76d3d90315bce55434
https://doi.org/10.1080/02331934.2019.1655738
https://doi.org/10.1080/02331934.2019.1655738