Optimization: Decisions with Constraints

Jeffrey M. Keisler
Additional contact information
Jeffrey M. Keisler: University of Massachusetts Boston

Chapter 9 in Prescriptive Analytics, 2024, pp 191-220 from Springer

Abstract: Abstract This chapter adds a new layer of detail to the Basic Business Model, assuming Widgets at one price are produced with a mix of labor and materials and Gadgets at a different price are produced with a different mix. If labor and material are limited, maximizing the objective of profit requires coordinated decisions about the quantities of the two products in the face of constraints. This chapter explores the concepts using stochastic approximation, which builds on simulation analysis in an intuitive and flexible way. This serves as a prelude to more formal mathematical programming optimization methods in the following chapter.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-031-59353-6_9

Ordering information: This item can be ordered from
http://www.springer.com/9783031593536

DOI: 10.1007/978-3-031-59353-6_9

Access Statistics for this chapter

More chapters in Springer Texts in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().