Multi Project Organization Optimization using Genetic Algorithm

Sven Tackenberg, Sebastian Schneider



Due to impatient customers and competitive threats, it has become increasingly important to shorten the lead time of development projects and to bring new products faster to the market. Furthermore, many organizations are faced with the challenge of planning and managing the simultaneous execution of multiple dependent projects under tight time and resource constraints. Within that kind of business environment, effective project management and scheduling is crucial to organizational performance. A genetic algorithm approach with a novel genotype and GP mapping operation is proposed to minimize the overall project duration and budget of multiple projects for a resource constrained multi project scheduling problem (RCMPSP) without violating inter-project resource constraints or intra-project precedence constraints. Stochastic rework of tasks, variable assignment of actors and stochastic makespan of a specific task are considered by the introduced GA. The proposed Genetic Algorithm is tested on scheduling problems with and without stochastic feedback. This GA demonstrates to provide a quick convergence to a global optimal solution regarding the multi-criteria objectives.


  1. Bäck, T., 1994. Selective Pressure in Evolutionary Algorithms: A Characterization of Selection Mechanisms. Proceedings of the First IEEE Conference on Evolutionary Computation, Vol. 1, 57-62.
  2. Brindle, A., 1981. Genetic Algorithms for Function Optimization. Doctoral dissertation, University of Alberta, Edmonton, Canada.
  3. Browning, T. R., and Eppinger, S. D., 2002. Modeling Impacts of Process Architecture on Cost and Schedule Risk in Product Development. In: IEEE Trans. Eng. Manage., 49(4), 428-442.
  4. Duckwitz, S., Licht, T., Schmitz, P., Schlick, C. M., 2008. Actor-Oriented, PersonCentered Simulation of Product Development Projects. In: Bertelle, C.; Ayesh, A. (Ed.). The 2008 European Simulation and Modelling Conference. Ghent, Belgien, EUROSIS-ETI, 66-73.
  5. Garey, M. R., Johnson, D. S., 1979. Computers and intractability: A guide to the theory of NP-completeness. W. H. Freeman & Co., New York
  6. Ghomi, S., Ashjari, B, 2002. A simulation model for multi-project resource allocation. In: International Journal of Project Management, 20(2), 127-130.
  7. Goncalves, J.F., Mendes, J.J.M., Resende, M.G.C., 2008. A genetic algorithm for the resource constrained multi-project scheduling problem. European Journal of Operations Research, 189, 1171-1190.
  8. Grünert, T., Irnich, S. 2005. Optimierung im Transport, Band 1: Grundlagen, 182-244. Shaker Verlag GmbH, Aachen.
  9. Hartmann, S., 1998. A competitive genetic algorithm for resource-constrained project scheduling. Naval Research Logistics, 45, 733-750.
  10. Hölltä-Otto, K., Magee, C. L., 2006. Estimating factors Affecting Project Task Size in Product Development - An Empirical Study. IEEE Trans. Engineering Management, 53(1), 86-94.
  11. Huberman, B.A., Wilkinson, D.M., 2005. Performance Variability and Project Dynamics. Computational & Mathematical Organization Theory, 11(4), 307-332.
  12. Kausch, B., Grandt, M., Schlick, C. 2007. Activity-based Optimization of Cooperative Development Processes in Chemical Engineering. In: SCSC 2007 “Summer Computer Simulation Conference”, 15-18 July 2007, San Diego.
  13. Kelley, J.E. Jr., 1961. Critical-Path Planning and Scheduling: Mathematical Basis. In: Operations Research, 9(3), 296-320.
  14. KHosraviani, B., 2005. An Evolutionary Approach for Project Organization Design: Producing Human Competitive Results Using Genetic Programming. Doctoral Dissertation, Department of Civil and Environmental Engineering, Stanford
  15. Kolisch, R., Padman, R., 2001. An integrated survey of project deterministic scheduling. In: International Journal of Management Science, 29(3), 249-272.
  16. Kolisch, R. (2000): Integrated scheduling, assembly area- and part-assignment for largescale, make-to-order assemblies. International Journal of Production Economies, 64, 127- 141.
  17. Kolisch, R., Hartmann, S. 1998. Heuristic algorithms for solving the resource constrained project scheduling problem: classification and computational analysis. In: Handbook on Recent Advances in Project Scheduling, Kluwer, Boston.
  18. Kummer, O., Wienberg, F., Duvigneau, M., 2006. Renew - the Reference Net Workshop. appeared as electronic version
  19. Lenstra, J., Rinnooy, K., 1978. Complexity of Scheduling under Precedence Constraints. Operations Research, 26(1), 22-35.
  20. Liepins, G.E., Vose, M.D. 1990. Representational issues in genetic optimization. In: Journal of Experimental and Theoretical Artificial Intelligence, 2(2), 4-30.
  21. Linyi, D.; Yan, L., 2007. A Particle Swarm Optimization for Resource-Constrained MultiProject Scheduling Problem. International Conference on Computational Intelligence and Security, doi:10.1109/CIS.2007.157.
  22. Malcolm, D.G., 1959. Application of a Technique for Research and Development Program Evaluation. In: Operations Research, 7(5), 646-669.
  23. Murata, T., Ishibuchi, H., 1994. Performance Evaluation of Genetic Algorithms for Flow Shop Scheduling Problems. In: Proceedings of the First IEEE Conference on Genetic Algorithms and their Applications Orlando, FL, June 27-29, 812-817.
  24. Nonobe, K., Ibaraki, T., 2001. A Local Search Approach to the Resource Constrained Project Scheduling Problem to Minimize Convex Costs. 4th Metaheuristics International Conference, Porto, Portugal.
  25. Schlick, C. M., Beutner, E., Duckwitz, S., Licht, T., 2007. A Complexity Measure for New Product Development Projects. In: Proceedings of the 19th International Engineering Management Conference, IEMC 2007, Managing Creativity: The Rise of the Creative Class. Austin, Texas, USA, 143-150.
  26. Shouman, M.A.; Ibrahim, M.S.; Khater, M.; Forgani, A.A., 2006. Genetic algorithm constraint project scheduling. Alexandria Engineering Journal, Vol. 45, No. 3, 289-298.
  27. Tackenberg, S., Kausch, B., Malabakan, A., Schlick, C. M., 2008. Organizational Simulation of Complex Process Engineering Projects in the Chemical Industry. In: Proceedings of the 2008 12th International Conference on Computer Supported Cooperative Work in Design Vol. II, April 16-18, 2008 Xi'an, China, IEEE Press, Beijing, 648-653.
  28. Thierens, D., 1995. Mixing in genetic algorithms. Doctoral Dissertation, Katholieke Universiteit Leuven
  29. Whitfield, R. I., Duffy, A. H. B., Coates, G., Hills, W., 2003. Efficient Process Optimization, Concurr. Eng. Res. Appl., 11(12), 83-92.
  30. Yang, B., Geunes, J., O'Brien, W.J., 2001. Resource-Constrained Project Scheduling: Past Work and New Directions. Research Report 2001-6, Department of Industrial and Sys. Engineering, University of Florida.
  31. Yassine, A. A., Meier, C., Browning, T. R. 2007a. Design Process Sequencing With Competent Genetic Algorithms. Transaction of the ASME, 129, 566-585.
  32. Yassine, A. A., Meier, C., Browning, T. R. 2007b. Multi-Project Scheduling using Competent Genetic Algorithms. Working Paper, University of Illinois
  33. Zhuang, M., Yassine, A. A., 2004. Task Scheduling of Parallel Development Projects Using Genetic Algorithms. In: Proceedings of DETC 04 ASME 2004, International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Salt Lake City, Utah, USA, 143-150

Paper Citation

in Harvard Style

Tackenberg S. and Schneider S. (2009). Multi Project Organization Optimization using Genetic Algorithm . In Proceedings of the 7th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems - Volume 1: MSVVEIS, (ICEIS 2009) ISBN 978-989-8111-90-6, pages 101-115. DOI: 10.5220/0002219801010115

in Bibtex Style

author={Sven Tackenberg and Sebastian Schneider},
title={Multi Project Organization Optimization using Genetic Algorithm},
booktitle={Proceedings of the 7th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems - Volume 1: MSVVEIS, (ICEIS 2009)},

in EndNote Style

JO - Proceedings of the 7th International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems - Volume 1: MSVVEIS, (ICEIS 2009)
TI - Multi Project Organization Optimization using Genetic Algorithm
SN - 978-989-8111-90-6
AU - Tackenberg S.
AU - Schneider S.
PY - 2009
SP - 101
EP - 115
DO - 10.5220/0002219801010115