Optimal Time-Table Generation by Hybridized Bacterial Foraging and Genetic Algorithms

Timetable scheduling is a highly constrained combinatorial NP-hard problem as has been described in the literature. A lot of constraints need to be accommodated for development of an efficient algorithm. This paper presents a hybrid approach to time table scheduling problem using bacterial foraging and genetic algorithm techniques. In the proposed algorithm, a bacterium represents a point in n-dimensional search space where each point is a potential solution to the timetable problem. The foraging behavior of E. Coli bacteria is simulated to search for an optimal solution. Genetic algorithm is used at the chemo taxis stage to give sense of biased-movement to the bacteria. Simulation results indicate that the proposed algorithm performs better as compared to the algorithms available in literature.