Scheduling problems are among the most challenging and realistic problems application of problem solving heuristics, such as genetic algorithms (GAs). The naive greedy algorithm for scheduling simply assigns, in turn, each item to be scheduled the best yet untaken position for that item. We investigate using a genetic algorithm to search the space of orderings for this greedy algorithm. That is, the GA individuals are permuations that determine the permutations that are the schedules, rather than the GA individuals directly being the schedules. We have experimented with the classical N Queens problem anda realistic soccer tournament scheduling problem, comparing the GA individual as the assignment with our greedy hybrid algorithm ( ordered greed ). Warnsdorff\u27s heuristic is introduced to modify blind greed with excellent results. We also introduce the use of signatures in our GAs to represent permutations. Signatures are easy to create and manipulate in crossover and mutation operations
