Quantitative Methods For Select Problems In Facility Location And Facility Logistics

<p>This dissertation presented three logistics problems. The first problem is a parallel machine scheduling problems that considers multiple unique characteristics including release dates, due dates, limited machine availability and job splitting. The objective of is to minimize the total amount of time required to complete work. A mixed integer programming model is presented and a heuristic is developed for solving the problem. The second problem extends the first parallel scheduling problem to include two additional practical considerations. The first is a setup time that occurs when warehouse staff change from one type of task to another. The second is a fixed time window for employee breaks. A simulated annealing (SA) heuristic is developed for its solution. The last problem studied in this dissertation is a new facility location problem variant with application in disaster relief with both verified data and unverified user-generated data are available for consideration during decision making. A total of three decision strategies that can be used by an emergency manager faced with a POD location decision for which both verified and unverified data are available are proposed: Consider Only Verified, Consider All and Consider Minimax Regret. The strategies differ according to how the uncertain user-generated data is incorporated in the planning process. A computational study to compare the performance of the three decision strategies across a range of plausible disaster scenarios is presented. </p>

Name thesis:degree_name

Doctor of Philosophy in Engineering (PhD)

Level thesis:degree_level

Dissertation

Year dc:date.available

2018

Author dc:creator

• Li, Bin

Advisor dc:contributor.advisor

• Milburn, Ashlea B.

Contributors dc:contributor

• Zhang, Shengfan
• Rainwater, Chase E.

• Facility Location
• Heuristics
• Simulated Annealing
• Industrial Engineering
• Industrial Technology
• Operational Research

Repository record dc:identifier

https://scholarworks.uark.edu/etd/2771

OAI identifier oai:identifier

oai:scholarworks.uark.edu:etd-4323