Active scheduling for hybrid flowshop with family setup time and inconsistent family formation

Hao Luo, Abraham Zhang, George Q. Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)


This research is motivated by a real-life hybrid flowshop scheduling problem where jobs are organized in families according to their machine settings and tools. This type of problem is common in the production process of standard metal components. The problem is complicated by the requirement of family setup time when a machine changes from processing one job family to another and the formation of job families varies in different stages. This problem has been previously solved with a non-delay scheduling heuristic in which no machine is kept idle. This research illustrates that inserting intentional idle time into a non-delay schedule can further reduce the total setup time as well as makespan. With the inserted idle time, the non-delay schedules are extended to active schedules. This paper presents a mechanism to determine the locations and lengths of intentional idle times in the efficient active schedules. Four active scheduling approaches are developed by integrating two types of waiting factor operators into two non-delay approaches. Computational experiments have been conducted to compare the proposed active scheduling approaches in terms of effectiveness and efficiency. The results have shown that the proposed active scheduling approaches are superior to non-delay scheduling. The analysis of variance has been applied on the factors related to scheduling environment, problem size and scheduling approach. The analysis has identified factors that are most influential on the scheduling result.

Original languageEnglish
Pages (from-to)169-187
Number of pages19
JournalJournal of Intelligent Manufacturing
Issue number1
Publication statusPublished - Feb 2013
Externally publishedYes


  • Active schedule
  • Family setup time
  • Hybrid flowshop scheduling
  • Inconsistent family formation
  • Non-delay schedule

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


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