Bacteria Foraging Optimization Algorithm for Robotic Cell Scheduling Problem

Abstract

The present study deals with the application of BFO for solving robotic cell problem. One of the major disadvantages of Passino invented BFO is its applicability constrains for solving problems except those contain continuous domain. Thus to make BFO applicable in robotic cell problem, Pairwiseinterchange mutation is chosen for tumbling and swimming operation during chemotaxis.While cyclic-shift neighbourhood mutation is used for random movement duringElimination-Dispersal. The example related to the two-machine robotic cell scheduling problem with sequence-dependent setup times (2RCSDST) was used to demonstrate the performance of the proposed discrete bacteria foraging algorithm. Large part sized problems varying from 200 to 500 part size was considered during this study. The computational results thus obtained were compared with two other existing optimization techniques and found BFO as the better performer to solve such large sized problems.