Parallel robot scheduling to minimize mean tardiness with precedence constraints using a genetic algorithm

Identical parallel robot scheduling problem for minimizing mean tardiness with precedence constraints is a very important scheduling problem. But, the solution of this problem becomes much difficult when there are a number of robots, jobs and precedence constraints. Genetic algorithm is an efficient tool in the solution of combinatorial optimization problems, as it is well known. In this study, a genetic algorithm is used to schedule jobs that have precedence constraints minimizing the mean tardiness on identical parallel robots. The solutions of problems, which have been taken in different scales, have been done using simulated annealing and genetic algorithm. In particular, genetic algorithm is found noteworthy successful in large-scale problems.