Minimizing makespan in a flow-line manufacturing cell with sequence dependent family setup times

Authors:
Hui-Miao Cheng;Kuo-Ching Ying
Affiliations:
Department of Information Management, China University of Technology, Taipei, Taiwan, ROC;Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 7
Cited 0

An Evolutionary Algorithm for Large Scale Set Covering Problems with Application to Airline Crew Scheduling

Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
Metaheuristics for scheduling a non-permutation flowline manufacturing cell with sequence dependent family setup times

Computers and Operations Research
Raising the hit rate for wafer fabrication by a simple constructive heuristic

Expert Systems with Applications: An International Journal
Sequencing single-machine tardiness problems with sequence dependent setup times using an iterated greedy heuristic

Expert Systems with Applications: An International Journal
Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups

Computers and Industrial Engineering - Special issue: Group technology/cellular manufacturing
Dynamic parallel machine scheduling with sequence-dependent setup times using an iterated greedy heuristic

Expert Systems with Applications: An International Journal
Two-machine group scheduling problems in discrete parts manufacturing with sequence-dependent setups

Computers and Operations Research

Quantified Score

Hi-index	12.05

Visualization

Abstract

The flow-line manufacturing cell scheduling problem (FMCSP) with sequence dependent family setup times (SDFSTs) is a topic of great concern for many industrial applications, but under-represented in the research literature. In this study, a two-level iterated greedy (TLIG) heuristic is proposed to minimize makespan of this strongly NP-hard problem. The performance of the proposed TLIG heuristic is compared against eight existing algorithms on a benchmark problem set used in earlier studies. The experimental results reveal that the proposed TLIG heuristic is very effective and efficient at finding near-optimal solutions for FMCSPs with SDFSTs.