Deadlock-free genetic scheduling algorithm for automated manufacturing systems based on deadlock control policy

Keyi Xing, Libin Han, Mengchu Zhou, Feng Wang

Research output: Contribution to journalArticlepeer-review

130 Scopus citations


Deadlock-free control and scheduling are vital for optimizing the performance of automated manufacturing systems (AMSs) with shared resources and route flexibility. Based on the Petri net models of AMSs, this paper embeds the optimal deadlock avoidance policy into the genetic algorithm and develops a novel deadlock-free genetic scheduling algorithm for AMSs. A possible solution of the scheduling problem is coded as a chromosome representation that is a permutation with repetition of parts. By using the one-step look-ahead method in the optimal deadlock control policy, the feasibility of a chromosome is checked, and infeasible chromosomes are amended into feasible ones, which can be easily decoded into a feasible deadlock-free schedule. The chromosome representation and polynomial complexity of checking and amending procedures together support the cooperative aspect of genetic search for scheduling problems strongly.

Original languageEnglish (US)
Article number6082462
Pages (from-to)603-615
Number of pages13
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number3
StatePublished - 2012

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Automated manufacturing systems (AMSs)
  • Petri net (PN)
  • deadlock avoidance policy (DAP)
  • genetic algorithm
  • scheduling


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