Make or Buy and Supplier Selection Problems in Make-To-Order Supply Chains

Haitao Li

doi:10.1007/978-3-319-05915-0__55

Make or Buy and Supplier Selection Problems in Make-To-Order Supply Chains

Haitao Li

University of Missouri-St. Louis

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Time- and cost-effective management of a make-to-order (MTO) supply chain often requires sourcing decisions, such as make-or-buy and supplier selection, to be jointly made with scheduling of supply chain operations. In this chapter, we introduce an RCPSP-based modeling framework to exploit the synergies and interactions between sourcing and scheduling decisions in MTO supply chains under explicit resource constraints. A mixed-integer nonlinear program (MINLP) is formulated to minimize the system wide total supply chain cost. We also present a numerical example to demonstrate the scope and depth of decision-support offered by the model for purchasing and program managers.

Original language	American English
Title of host publication	Handbook on Project Management and Scheduling Vol. 2
DOIs	https://doi.org/10.1007/978-3-319-05915-0__55
State	Published - Oct 2015

Disciplines

Business Administration, Management, and Operations

Access to Document

10.1007/978-3-319-05915-0__55License: Unspecified

Handbook_Chap55.pdfFinal published version, 706 KBLicense: Unspecified

Cite this

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title = "Make or Buy and Supplier Selection Problems in Make-To-Order Supply Chains",

abstract = " Time- and cost-effective management of a make-to-order (MTO) supply chain often requires sourcing decisions, such as make-or-buy and supplier selection, to be jointly made with scheduling of supply chain operations. In this chapter, we introduce an RCPSP-based modeling framework to exploit the synergies and interactions between sourcing and scheduling decisions in MTO supply chains under explicit resource constraints. A mixed-integer nonlinear program (MINLP) is formulated to minimize the system wide total supply chain cost. We also present a numerical example to demonstrate the scope and depth of decision-support offered by the model for purchasing and program managers.",

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