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An evolutionary algorithm for the resource-constrained project scheduling problem with minimum and maximum time lags

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Abstract

In this paper, we present an evolutionary algorithm (EVA) for solving the resource-constrained project scheduling problem with minimum and maximum time lags (RCPSP/max). EVA works on a population consisting of several distance-order-preserving activity lists representing feasible or infeasible schedules. The algorithm uses the conglomerate-based crossover operator, the objective of which is to exploit the knowledge of the problem to identify and combine those good parts of the solution that have really contributed to its quality. In a recent paper, Valls et al. (European J. Oper. Res. 165, 375–386, 2005) showed that incorporating a technique called double justification (DJ) in RCPSP heuristic algorithms can produce a substantial improvement in the results obtained. EVA also applies two double justification operators DJmax and DJU adapted to the specific characteristics of problem RCPSP/max to improve all solutions generated in the evolutionary process. Computational results in benchmark sets show the merit of the proposed solution method.

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References

  • Ballestín, F. (2002). Nuevos métodos de resolución del problema de secuenciación de proyectos con recursos limitados. Unpublished PhD Dissertation, Universidad de Valencia.

  • Bartusch, M., Möhring, R. H., & Radermacher, F. J. (1988). Scheduling project networks with resource constraints and time windows. Annals of Operations Research, 16, 201–240. doi:10.1007/sBF02283745.

    Article  Google Scholar 

  • Cesta, A., Oddi, A., & Smith, S. (2002). A constraint based method for project scheduling with time windows. Journal of Heuristics, 8(1), 109–136. doi:10.1023/A:1013617802515.

    Article  Google Scholar 

  • Cicirello, V. A. (2003). Boosting stochastic problem solvers through online self-analysis of performance. PhD thesis, The Robotics Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh. Also available as a technical report CMU-RI-TR-03-27.

  • Cicirello, V. A., & Smith, S. (2004). Heuristic selection for stochastic search optimization. In Lecture notes in computer science. Modeling solution quality by extreme value (Vol. 23, pp. 197–211). Berlin: Springer.

    Google Scholar 

  • De Reyck, B., & Herroelen, W. (1998). A branch-and-bound procedure for the resource-constrained project scheduling problem with generalized precedence constraints. European Operational Research, 111, 152–174. doi:10.1016/S0377-2217(97)00305-6.

    Article  Google Scholar 

  • Dorndorf, U., Pesch, E., & Phan-Huy, T. (2000). A time-oriented branch-and-bound algorithm for resource-constrained project scheduling with generalised precedence constraints. Management Science, 46, 1365–1384. doi:10.1287/mnsc.46.10.1365.12272.

    Article  Google Scholar 

  • Drexl, A. (1991). Scheduling of project networks by job assignment. Management Science, 37, 1590–1602. doi:10.1287/mnsc.37.12.1590.

    Article  Google Scholar 

  • Fest, A., Möhring, R. H., Stork, F., & Uetz, M. (1998). Resource-constrained project scheduling with time windows: a branching scheme based on dynamic release dates. Technical report 596, TU Berlin, Germany.

  • Franck, B., & Neumann, K. (1998). Resource constrained project scheduling problems with time windows—structural questions and priority-rule methods. Technical report WIOR 492, Universität Karlsruhe.

  • Franck, B., Neumann, K., & Schwindt, Ch. (2001). Truncated branch and bound, schedule construction, and schedule improvement procedures for resource constrained project scheduling. In OR Specktrum (Vol. 23, pp. 297–324). Berlin: Springer.

    Google Scholar 

  • Hartmann, S. (1998). A competitive genetic algorithm for resource-constrained project scheduling. Naval Research Logistics, 45, 733–750. doi:10.1002/(SICI)1520-6750(199810)45:7<733::AID-NAV5>3.0.CO;2-C.

    Article  Google Scholar 

  • Kolisch, R., & Hartmann, S. (1999). Heuristic algorithms for solving the resource-constrained project scheduling problem: classification and computational analysis. In J. Weglarz (Ed.), Project scheduling, recent models, algorithms and applications (pp. 147–178). Boston: Kluwer Academic.

    Google Scholar 

  • Kolisch, R., & Hartmann, S. (2006). Experimental investigation of heuristics for resource-constrained project scheduling: an update. European Journal of Operational Research, 174, 23–37. doi:10.1016/j.ejor.2005.01.065.

    Article  Google Scholar 

  • Luo, S., Wang, C., & Wang, J. (2003). Ant colony optimization for resource-constrained project scheduling with generalized precedence relations. In Proceedings of the 15th IEEE international conference on tools with artificial intelligence (ICTAI’03).

  • Neumann, K. (1975). Operations research verfahren, Band III. München: Carl Hanser.

    Google Scholar 

  • Neumann, K., & Schwindt, C. (1995). Projects with minimal and maximal time lags: construction of activity on-node networks and applications. Report WIOR-447, University of Karlsruhe.

  • Neumann, K., Schwindt, Ch., & Zimmermann, J. (2002). Project Scheduling with Time Windows and Scarce Resources. Berlin: Springer.

    Google Scholar 

  • Smith, T. (2004). Windows-based project scheduling algorithms. PhD thesis, University of Oregon.

  • Schwindt, C. (1996). Generation of resource constrained project scheduling problems with minimal and maximal time lags. Report WIOR 489, Institute for Economic Theory and Operations Research, University of Karlsruhe.

  • Schwindt, C. (1998). A branch-and-bound algorithm for the resource-constrained project duration problem subject to temporal constraints. Technical report, WIOR-544, University Karlsruhe, Germany.

  • Tarjan, R. (1972). Depth-first search and linear graph algorithms. SIAM Journal of Computing, 1, 146–160. doi:10.1137/0201010.

    Article  Google Scholar 

  • Valls, V., Ballestín, F., & Quintanilla, S. (2005). Justification and RCPSP: a technique that pays. European Journal of Operational Research, 165, 375–386. doi:10.1016/j.ejor.2004.04.008.

    Article  Google Scholar 

  • Valls, V., Ballestín, F., & Quintanilla, S. (2008). A hybrid genetic algorithm for the resource-constrained project scheduling problem. European Journal of Operational Research, 185, 495–508. doi:10.1016/j.ejor.2006.12.033.

    Article  Google Scholar 

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Authors and Affiliations

  1. Dept. de Estadística e Investigación Operativa, Universidad Pública de Navarra, 31006, Pamplona, Spain

    Francisco Ballestín

  2. Dept. de Matemáticas y Física, Universidad del Norte, Barranquilla, Colombia

    Agustín Barrios

  3. Dept. de Estadística e Investigación Operativa, Universidad de Valencia, 46100, Burjasot, Spain

    Vicente Valls

Authors
  1. Francisco Ballestín
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  2. Agustín Barrios
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  3. Vicente Valls
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Correspondence to Francisco Ballestín.

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Ballestín, F., Barrios, A. & Valls, V. An evolutionary algorithm for the resource-constrained project scheduling problem with minimum and maximum time lags. J Sched 14, 391–406 (2011). https://doi.org/10.1007/s10951-009-0125-9

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  • DOI: https://doi.org/10.1007/s10951-009-0125-9

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