Abstract
Abstract Because of the difficulty in computing the bivariate integral originated from the correlated demand and price, most research work on uncertainty assumes that the demand and price are independent. This can cause significant discrepancies in revenue calculation and hence yield sub-optimal planning strategies. This paper presents a novel approach to handle correlated and truncated demand and price uncertainties. A bivariate normal distribution is used to describe demand and price. The double integral for unintegrable standard normal cumulative distribution function in the single integrals is approximated by polynomial functions. Case studies show that, assuming independent price and demand may underestimate the revenue by up to 20%. Since the real world demands or prices vary in limited ranges, integrating over the whole range of a normal distribution, which some research has done, may give incorrect results. This paper uses a bivariate double-truncated normal distribution to describe demand and price. The influence of different degrees of truncation on plant revenue is studied.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
