ENHANCED BACTERIAL FORAGING ALGORITHM FOR PERMUTATION FLOW SHOP SCHEDULING PROBLEMS

Biologically Inspired algorithms are a kind of algorithms that imitate the problem solving behavior from biological species. Bio-inspired computing is a subset of Nature-inspired computing that focus on social behavior and emergence of biological species. Bacterial Foraging algorithm is a relatively new biologically inspired optimization technique based on the foraging behaviour of E. coli bacteria. This paper deals with one of the significant types of scheduling problems, the permutation flow shop scheduling problem. The competence of bacterial problem solving and a proposed hybrid bacterial swarming technique were analyzed by applying them to benchmark problems of permutation flow shop. A comparative analysis of the results indicates the improvement in scheduling efficiency in tenns of reduced cost through the application of bio-inspired techniques.