Genetic algorithm to production planning and scheduling problems for manufacturing systems

Ying LI, Kim Fung MAN, Kit Sang TANG, Sam KWONG, W. H. IP

Research output: Journal PublicationsJournal Article (refereed)peer-review

37 Citations (Scopus)


Fundamental and extended multi-objective (MO) models are designed to address earliness/tardiness production scheduling planning (ETPSP) problems with multi-process capacity balance, multi-product production and lot-size consideration. A canonical genetic algorithm (GA) approach and a prospective multi-objective GA (MOGA) approach are proposed as solutions for different practical problems. Simulation results as well as comparisons with other techniques demonstrate the effectiveness of the MOGA approach, which is a noted improvement to any of the existing techniques, and also in practice provides a new trend of integrating manufacturing resource planning (MRPII) with just-in-time (JIT) in the production planning procedure.
Original languageEnglish
Pages (from-to)443-458
JournalProduction Planning and Control
Issue number5
Publication statusPublished - Jul 2000
Externally publishedYes


  • Earliness/tardiness production scheduling and planning (ETPSP)
  • Genetic algorithms (GAs)
  • Multi-objective (MO)
  • Optimization
  • Production/inventory management and control (PIMC)


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