Computational studies of stochastic optimization algorithms for process synthesis under uncertainty Academic Article

abstract

• In this paper, stochastic optimization algorithms are presented to address process synthesis problems under uncertainty. Alternative integration schemes are proposed, their theoretical implications are discussed, and their computational performance on serial and parallel computers are studied on several example problems.

authors

• Pistikopoulos, Stratos

published proceedings

• COMPUTERS & CHEMICAL ENGINEERING

author list (cited authors)

• Acevedo, J., & Pistikopoulos, E. N.

citation count

• 17

complete list of authors

• Acevedo, J||Pistikopoulos, EN

publication date

• January 1996

publisher

• Elsevier  Publisher

published in

• Computers and Chemical Engineering  Journal

keywords

• Networking And Information Technology R&d

Digital Object Identifier (DOI)

• 10.1016/0098-1354(96)00011-7

start page

• S1

end page

• S6

volume

• 20

issue

• SUPPL.1

URL

• http://dx.doi.org/10.1016/0098-1354(96)00011-7