Open AccessConstraint programing for solving four complex flexible shop scheduling problems
Author(s) -
Meng Leilei,
Lu Chao,
Zhang Biao,
Ren Yaping,
Lv Chang,
Sang Hongyan,
Li Junqing,
Zhang Chaoyong
Publication year - 2021
Publication title -
iet collaborative intelligent manufacturing
Language(s) - English
Resource type - Journals
ISSN - 2516-8398
DOI - 10.1049/cim2.12005
Subject(s) - job shop scheduling , flow shop scheduling , computer science , mathematical optimization , nurse scheduling problem , scheduling (production processes) , fair share scheduling , benchmark (surveying) , rate monotonic scheduling , two level scheduling , dynamic priority scheduling , mathematics , schedule , geodesy , geography , operating system
In recent years, with the advent of robust solvers such as Cplex and Gurobi, constraint programing (CP) has been widely applied to a variety of scheduling problems. This paper presents CP models for formulating four scheduling problems with minimal makespan and complex constraints: the no‐wait hybrid flow shop scheduling problem, the hybrid flow shop scheduling problem with sequence‐dependent setup times, the flexible job shop scheduling problem with worker flexibility and the semiconductor final testing problem. The advantages of CP method in solving these four complex scheduling problems are explored. Finally, a set of benchmark instances are adopted to demonstrate the effectiveness and efficiency of the CP method. Experiment results show that the proposed CP models outperform existing algorithms; in particular, several best‐known solutions of benchmark instances are improved by our CP method.