Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case study in Quadratic Assignment Problem

• Main Authors: LINDAWATI, Linda, Yuan, Zhi, LAU, Hoong Chuin, ZHU, Feida
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: automated parameter tuning; instance-specific parameter configuration; parameter search space reduction; large instance parameter tuning; Artificial Intelligence and Robotics; Business; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/1657; https://ink.library.smu.edu.sg/context/sis_research/article/2656/viewcontent/Lindawati_Yuan_Lau_Zhu_Automated_20Parameter_20Tuning.pdf
• Institution: Singapore Management University

This paper is concerned with automated tuning of parameters of algorithms to handle heterogeneous and large instances. We propose an automated parameter tuning framework with the capability to provide instance-specific parameter configurations. We report preliminary results on the Quadratic Assignment Problem (QAP) and show that our framework provides a significant improvement on solutions qualities with much smaller tuning computational time.