A block-based evolutionary algorithm for flow-shop scheduling problem

Pei Chann Chang, Meng Hui Chen, Manoj K. Tiwari, Asif Sikandar Iquebal

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Combinatorial problems like flow shop scheduling, travel salesman problem etc. get complicated and are difficult to solve when the problem size increases. To overcome this problem, we present a block-based evolutionary algorithm (BBEA) which will conduct evolutionary operations on a set of blocks instead of genes. BBEA includes the block mining and block recombination approaches. A block mining algorithm is developed to decompose a chromosome into a set of blocks and rest of genes. The block is with a fixed length and can be treated as a building block in forming a new chromosome later on. To guide the block mining process, a gene linkage probability matrix is defined that shows the linkage strength among genes. Therefore the blocks can be further evolved during the evolutionary processes using this matrix. In the block recombination approach, the blocks along with the rest of genes are recombined to form a new chromosome. This new evolutionary approach of BBEA is tested on a set of discrete problems. Experimental results show that BBEA is very competitive when compared with traditional GA, EA or ACGA and HGIA approaches and it can largely improve the performance of evolutionary algorithm and save a fair amount of computational times simultaneously.

Original languageEnglish (US)
Pages (from-to)4536-4547
Number of pages12
JournalApplied Soft Computing Journal
Issue number12
StatePublished - 2013
Externally publishedYes


  • Building blocks
  • Combinatorial optimization problem
  • Evolutionary algorithm
  • Gene linkage
  • Recombination

ASJC Scopus subject areas

  • Software


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