TY - GEN
T1 - Non-integrated algorithm based on EDA and Tabu Search for test task scheduling problem
AU - Lu, Hui
AU - Zhang, Mengmeng
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/14
Y1 - 2015/12/14
N2 - The optimization of test task scheduling problem (TTSP) is an important issue in automatic test system (ATS). TTSP is a complex combination optimization problem and includes two sub-problems. They are test task sequencing and test scheme combination. According to the characteristic of TTSP, a non-integrated algorithm based on estimation of distribution algorithm and Tabu Search (EDA-TS) is proposed in this paper. EDA focuses on solving test task sequencing in global searching, and TS emphasizes on solving test scheme combination in local searching. In addition, we give a mathematical model for TTSP. We prove that TTSP is an NPhard by using traveling salesman problem (TSP) based on the mathematical model. The statistical results of single objective TTSP suggest that our approach has a stronger searching ability and good convergence compared with other three popular algorithms. The experiments of the multi-objectives TTSP also illustrate that EDA-TS has a strong searching ability and can maintain a diversity of solutions.
AB - The optimization of test task scheduling problem (TTSP) is an important issue in automatic test system (ATS). TTSP is a complex combination optimization problem and includes two sub-problems. They are test task sequencing and test scheme combination. According to the characteristic of TTSP, a non-integrated algorithm based on estimation of distribution algorithm and Tabu Search (EDA-TS) is proposed in this paper. EDA focuses on solving test task sequencing in global searching, and TS emphasizes on solving test scheme combination in local searching. In addition, we give a mathematical model for TTSP. We prove that TTSP is an NPhard by using traveling salesman problem (TSP) based on the mathematical model. The statistical results of single objective TTSP suggest that our approach has a stronger searching ability and good convergence compared with other three popular algorithms. The experiments of the multi-objectives TTSP also illustrate that EDA-TS has a strong searching ability and can maintain a diversity of solutions.
KW - estimation of distribution algorithm
KW - NP-hard
KW - Tabu Search
KW - test task scheduling problem
UR - https://www.scopus.com/pages/publications/84959929666
U2 - 10.1109/AUTEST.2015.7356500
DO - 10.1109/AUTEST.2015.7356500
M3 - 会议稿件
AN - SCOPUS:84959929666
T3 - AUTOTESTCON (Proceedings)
SP - 261
EP - 268
BT - IEEE Autotestcon 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 51st IEEE Autotestcon 2015, AUTOTESTCON 2015
Y2 - 2 November 2015 through 4 November 2015
ER -