A Multi-Objective Affinity-Based Savings Algorithm for Improving Processes in Centralized Warehousing Operations
Date of Graduation
Master of Science in Industrial Engineering (MSIE)
Second Committee Member
Batching, Facility, Logistics, Operations, Process Planning, Warehousing
Traditional approaches to improving material management processes in warehousing operations tend to focus on one of three major areas: facility design, order picking and sorting, and order batching. In an effort to improve total system savings, a new affinity function is developed and applied to batching logic to create a multi-objective problem. The proposed multi-objective function incorporates user input to increase adaptability to changing demand and flexibility to changing requirements. Computational experience shows the new function leads to solutions that deviate no more than 25% from the most efficient distance based picking route by the same batching logic, while creating savings in the sorting process at the centralized warehouse. The new function reduces savings loss from noncompliance of order pickers through its multi-objective design and is quick to respond to a rapidly changing climate by effective user input. The promising results of the proposed function open the door for additional objectives to be applied to the same logic to expand the objective to include goals like on-time performance.
Coco, M. M. (2018). A Multi-Objective Affinity-Based Savings Algorithm for Improving Processes in Centralized Warehousing Operations. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/2725