Integer Programming for Discrete Optimization of the Agile Supply Chain Configuration Problem

In order to keep manufacturing operations in lockstep with current market trends, businesses must continue to incorporate agility into their supply chains. This includes the ability to assess and select new suppliers quickly. The Digital Manufacturing Market (DMM) and Manufacturing Service Description Language (MSDL) have been devised previously as the necessary IT components for improving the intelligence of the supply chain configuration process. The objective of this research is to enhance the performance of the DMM's search engine by incorporating combinatorial optimization techniques. In particular, this research is aimed at creating an integer programming formulation to efficiently and effectively solve the supply chain configuration problem by maximizing the technological competencies of the assigned suppliers, while meeting capacity and distance constraints. The column generation approach is adopted to resolve the issue of limited scalability of the traditional LP formulation. Vendor cuts are proposed as a method to constrain distance inside the supply chain network. The proposed column generation formulation successfully enables transition from a computationally prohibitive methodology to a fully scalable model that maintains functionality at very large sizes. The results also show that it is possible to achieve an economy of distance with little effect on match compatibility.

Name thesis:degree_name

Master of Science in Technology

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Industrial Technology

Grantor

Texas State University-San Marcos

Year dc:date.issued

2013

Author dc:creator

• Beauchamp, Hayden D.

Advisor dc:contributor.advisor

• Ameri, Farhad

Committee members dc:contributor.committeemember

• Novoa, Clara
• Sriraman, Vedaraman

• discrete optimization
• integer programming
• supplier selection problem
• generalized assignment problem
• column generation

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10877/4614

OAI identifier oai:identifier

oai:digital.library.txst.edu:10877/4614