A genetic algorithm for project scheduling

This study presents a genetic algorithm for the resource constrained project scheduling problem using Delphi 6. Resource constrained project scheduling is one of the NP-hard classes because of the complexity of their combinatorial nature. Any exact algorithm are difficult to handle such a problem.The heuristic algorithm generates parameterized active schedules and selects the best one which has minimum project completion time among the generated schedules. The chromosome representation of the problem is based on the both random key and priority rule represantation. The schedule is constructed using randomly selected heuristic priority rule.Priorities of activities of scheduling problems are given by two types such as proccessors/successors of any activities. The algorithm works for two types of scheduling problems. So there is no need any conversion process for successors to proccessors ( or vice versa ) by human being.The algorithm was tested on the four sets of standard problems from the literature. Each set has many project scheduling problems. Total number of scheduling problems is 2040. Each of these scheduling problems are tested twice to observe the effects of different iteration number.To measure and evaluate the performance of the algorthm; the average deviation of each problem set is calculated to compare the algorithm with other approaches in the literature. The computational results are reported.Computational results relatively validate the effectiveness of the generated algortihm. Generally, the algorithm gives global results for simple problems and gives local results for complex problems.