A genetic algorithm for the project scheduling with the resource constraints

The resource-constrained project scheduling problem (RCPSP) has received the attention of many researchers because it can be applied in a wide variety of real production and construction projects. This paper presents a genetic algorithm (GA) solving the RCPSP with the objective function of minimizing makespan. Standard genetic algorithm has to be adapted for project scheduling with precedence constraints. Therefore, an initial population was generated by a random procedure which produces feasible solutions (permutation of jobs fulfilling precedence constraints). Besides, all implemented genetic operators have taken sequential relationships in a project into consideration. Finally, we have demonstrated the performance and accuracy of the proposed algorithm. Computational experiments were performed using a set of 960 standard problem instances from Project Scheduling Problem LIBrary (PSPLIB) presented by Kolisch and Sprecher [1]. We used 480 problems consisting of 30 jobs and 480 90-activity instances. We have tested effectiveness of various combinations of parameters, genetic operators to find the best configuration of GA. The computational results validate the good effectiveness of our genetic algorithm.

[1]  Erik Demeulemeester,et al.  Resource-constrained project scheduling: A survey of recent developments , 1998, Comput. Oper. Res..

[2]  R. Kolisch,et al.  Heuristic algorithms for solving the resource-constrained project scheduling problem: Classification and computational analysis , 1998 .

[3]  Zbigniew Michalewicz,et al.  Genetic Algorithms Plus Data Structures Equals Evolution Programs , 1994 .

[4]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[5]  Jan Karel Lenstra,et al.  Scheduling subject to resource constraints: classification and complexity , 1983, Discret. Appl. Math..

[6]  Michael de la Maza,et al.  Book review: Genetic Algorithms + Data Structures = Evolution Programs by Zbigniew Michalewicz (Springer-Verlag, 1992) , 1993 .

[7]  R. Kolisch,et al.  Heuristic algorithms for the resource-constrained project scheduling problem: classification and computational analysis , 1999 .

[8]  Rainer Kolisch,et al.  Experimental investigation of heuristics for resource-constrained project scheduling: An update , 2006, Eur. J. Oper. Res..

[9]  Rainer Kolisch,et al.  PSPLIB - A project scheduling problem library: OR Software - ORSEP Operations Research Software Exchange Program , 1997 .

[10]  Rainer Kolisch.  Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation , 1994 .

[11]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[12]  BierwirthChristian,et al.  Production scheduling and rescheduling with genetic algorithms , 1999 .

[13]  Christian Bierwirth,et al.  Production Scheduling and Rescheduling with Genetic Algorithms , 1999, Evolutionary Computation.