Integrated Optimization of Procurement, Processing and Trade of Commodities in a Network Environment
dc.contributor.author | Devalkar, Sripad Krishnaji | |
dc.contributor | Anupindi, Ravi | |
dc.contributor | Sinha, Amitabh | |
dc.date.accessioned | 2007-08-03T15:58:10Z | |
dc.date.available | 2007-08-03T15:58:10Z | |
dc.date.issued | 2010-04 | |
dc.identifier | 1095 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/55417 | |
dc.description.abstract | We consider the integrated optimization problem of procurement, processing and trade of commodities over a network in a multiperiod setting. Motivated by the operations of a prominent commodity processing firm, we model a firm that operates a star network with multiple locations at which it can procure an input commodity and has processing capacity at a central location to convert the input into a processed commodity. The processed commodity is sold using forward contracts, while the input itself can be traded at the end of the horizon. We show that the single-node version of this problem can be solved optimally when the procurement cost for the input is piecewise linear and convex, and derive closed form expressions for the marginal value of input and output inventory. However, these marginal values are hard to compute because of high dimensionality of the state space and we develop an efficient heuristic to compute approximate marginal values. We also show that the star network problem can be approximated as an equivalent single node problem and propose heuristics for solving the network problem. We conduct numerical studies to evaluate the performance of both the single node and network heuristics. We find that the single node heuristics are near-optimal, capturing close to 90% of the value of an upper bound on the optimal expected profits. Approximating the star network by a single node is effective, with the gap between the heuristic and upper bound ranging from 7% to 14% for longer planning horizons | en_US |
dc.format.extent | 384280 bytes | |
dc.format.mimetype | application/pdf | |
dc.subject | Integrated Optimization, Commodities, Network | en_US |
dc.subject.classification | Operations and Management Science | en_US |
dc.title | Integrated Optimization of Procurement, Processing and Trade of Commodities in a Network Environment | en_US |
dc.type | Working Paper | en_US |
dc.subject.hlbsecondlevel | Economics | en_US |
dc.subject.hlbtoplevel | Business | en_US |
dc.contributor.affiliationum | Ross School of Business | en_US |
dc.contributor.affiliationother | Ross School of Business | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/55417/1/1095-Anupindi.pdf | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/55417/4/1095-Anupindi_2010.pdf | |
dc.owningcollname | Business, Stephen M. Ross School of - Working Papers Series |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.