Optimization of Scheduling Problems: A genetic algorithm survey

There are various methods to optimize the scheduling systems such as tabu search, genetic algorithms and simulated annealing etc. These methods usually require much less work than developing a specialized heuristic for a specific application, which makes metaheuristics an appealing choice for implementation in general purpose of sequencing and scheduling. Furthermore, a good metaheuristics implementation is likely to provide near optimal solutions in reasonable computational time. Among these Genetic algorithm is believed to be the most vigorous impartial random (stochastic) search algorithm for sampling a large solution space. This study demonstrates a substantial description of various genetic algorithm based techniques and its usage in scheduling and sequencing problem. A review of genetic algorithm and its intricate practices in managing different objective problems and forming hybrid procedures with parameters for scheduling problems have been explored in the present work.