How to cite this paper
Rahmani, N., Zeighami, V & Akbari, R. (2015). A study on the performance of differential search algorithm for single mode resource constrained project scheduling problem.Decision Science Letters , 4(4), 537-550.
Refrences
Agarwal, A., Colak, S., & Erenguc, S. (2011). A neurogenetic approach for the resource-constrained project scheduling problem. Computers & Operations Research, 38(1), 44-50.
Akbari, R., Zeighami, V., & Ziarati, K. (2011). Artificial bee colony for resource constrained project scheduling problem. International Journal of Industrial Engineering Computations, 2(1), 45-60.
Akbari, R., Zeighami, V., & Akbari, I. (2012). An ABC-Genetic method to solve resource constrained project scheduling problem. Artificial Intelligence Research, 1(2), p185.
Alcaraz, J., & Maroto, C. (2001). A robust genetic algorithm for resource allocation in project scheduling. Annals of Operations Research, 102(1-4), 83-109.
Baar, T., Brucker, P., & Knust, S. (1999). Tabu search algorithms and lower bounds for the resource-constrained project scheduling problem (pp. 1-18). Springer US.
Bouleimen K. and Lecocq H.. (2003). A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research, 149(2), 268-281.
Chen, W., Shi, Y. J., Teng, H. F., Lan, X. P., & Hu, L. C. (2010). An efficient hybrid algorithm for resource-constrained project scheduling. Information Sciences, 180(6), 1031-1039.
Chen, R. M., Wu, C. L., Wang, C. M., & Lo, S. T. (2010). Using novel particle swarm optimization scheme to solve resource-constrained scheduling problem in PSPLIB. Expert systems with applications, 37(3), 1899-1910.
Civicioglu, P. (2012). Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm. Computers & Geosciences,46, 229-247.
Coelho, J., & Vanhoucke, M. (2011). Multi-mode resource-constrained project scheduling using RCPSP and SAT solvers. European Journal of Operational Research, 213(1), 73-82.
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(10), 1365-1384.
Fahmy, A., Hassan, T. M., & Bassioni, H. (2014). Improving RCPSP solutions quality with Stacking Justification–Application with particle swarm optimization. Expert Systems with Applications, 41(13), 5870-5881.
Hartmann, S., & Kolisch, R. (2000). Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem. European Journal of Operational Research, 127(2), 394-407.
Hartmann, S. (1998). A competitive genetic algorithm for resource?constrained project scheduling. Naval Research Logistics (NRL), 45(7), 733-750.
Hartmann, S. (2002). A self?adapting genetic algorithm for project scheduling under resource constraints. Naval Research Logistics (NRL), 49(5), 433-448.
Herbots, J., Herroelen, W., & Leus, R. (2004). Experimental investigation of the applicability of ant colony optimization algorithms for project scheduling. DTEW Research Report 0459, 1-25.
Jarboui, B., Damak, N., Siarry, P., & Rebai, A. (2008). A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems. Applied Mathematics and Computation, 195(1), 299-308.
Jia, Q., & Seo, Y. (2013). Solving resource-constrained project scheduling problems: conceptual validation of FLP formulation and efficient permutation-based ABC computation. Computers & Operations Research, 40(8), 2037-2050.
Jia, Q., & Seo, Y. (2013). An improved particle swarm optimization for the resource-constrained project scheduling problem. The International Journal of Advanced Manufacturing Technology, 67(9-12), 2627-2638.
Koulinas, G., Kotsikas, L., & Anagnostopoulos, K. (2014). A particle swarm optimization based hyper-heuristic algorithm for the classic resource constrained project scheduling problem. Information Sciences, 277, 680-693.
Kolisch, R. (1996). Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation. European Journal of Operational Research, 90(2), 320-333.
Kolisch, R., & Hartmann, S. (2006). Experimental investigation of heuristics for resource-constrained project scheduling: An update. European journal of operational research, 174(1), 23-37.
Kolisch, R., & Hartmann, S. (1999). Heuristic algorithms for the resource-constrained project scheduling problem: Classification and computational analysis (pp. 147-178). Springer US.
Kolisch, R., & Padman, R. (2001). An integrated survey of deterministic project scheduling. Omega, 29(3), 249-272.
Kumar, N. (2014). Study on meta-heuristics for resource constrained project scheduling problem. International Journal of Engineering, Management & Sciences, 1(2), 14-24.
Luo, X., Wang, D., Tang, J., & Tu, Y. (2006, June). An improved pso algorithm for resource-constrained project scheduling problem. In Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on (Vol. 1, pp. 3514-3518). IEEE.
Mendes, J. J. D. M., Gonçalves, J. F., & Resende, M. G. (2009). A random key based genetic algorithm for the resource constrained project scheduling problem. Computers & Operations Research, 36(1), 92-109.
Merkle, D., Middendorf, M., & Schmeck, H. (2002). Ant colony optimization for resource-constrained project scheduling. Evolutionary Computation, IEEE Transactions on, 6(4), 333-346.
Nasiri, M. M. (2013). A pseudo particle swarm optimization for the RCPSP. The International Journal of Advanced Manufacturing Technology, 65(5-8), 909-918.
Neumann, K., & Zimmermann, J. (1999). Methods for resource-constrained project scheduling with regular and nonregular objective functions and schedule-dependent time windows. In Project Scheduling (pp. 261-287). Springer US.
Nonobe, K., & Ibaraki, T. (2002). Formulation and tabu search algorithm for the resource constrained project scheduling problem. In Essays and surveys in metaheuristics (pp. 557-588). Springer US.
Orji, I. M., & Wei, S. (2013, April). Project scheduling under resource constraints: a recent survey. In International Journal of Engineering Research and Technology (Vol. 2, No. 2 (February-2013)). ESRSA Publications.
Ranjbar, M., Kianfar, F., & Shadrokh, S. (2008). Solving the resource availability cost problem in project scheduling by path relinking and genetic algorithm. Applied Mathematics and Computation, 196(2), 879-888.
Sanaei, P., Akbari, R., Zeighami, V., & Shams, S. (2013, January). Using firefly algorithm to solve resource constrained project scheduling problem. InProceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) (pp. 417-428). Springer India.
Schirmer, A. (2000). Case?based reasoning and improved adaptive search for project scheduling. Naval Research Logistics (NRL), 47(3), 201-222.
Shou, Y., Li, Y., & Lai, C. (2015). Hybrid particle swarm optimization for preemptive resource-constrained project scheduling. Neurocomputing, 148, 122-128.
Tseng, L. Y., & Chen, S. C. (2006). A hybrid metaheuristic for the resource-constrained project scheduling problem. European Journal of Operational Research, 175(2), 707-721.
Valls, V., Ballest??n, F., & Quintanilla, S. (2005). Justification and RCPSP: A technique that pays. European Journal of Operational Research, 165(2), 375-386.
Valls, V., Ballestin, F., & Quintanilla, S. (2008). A hybrid genetic algorithm for the resource-constrained project scheduling problem. European Journal of Operational Research, 185(2), 495-508.
Xiao, L., Tian, J., & Liu, Z. (2014, June). An Activity-List based Nested Partitions algorithm for Resource-Constrained Project Scheduling. In Intelligent Control and Automation (WCICA), 2014 11th World Congress on (pp. 3450-3454). IEEE.
Yang, B., Geunes, J., & O’brien, W. J. (2001). Resource-constrained project scheduling: Past work and new directions. Department of Industrial and Systems Engineering, University of Florida, Tech. Rep.
Zamani, R. (2013). A competitive magnet-based genetic algorithm for solving the resource-constrained project scheduling problem. European Journal of Operational Research, 229(2), 552-559.
Zhang, H., Li, X., Li, H., & Huang, F. (2005). Particle swarm optimization-based schemes for resource-constrained project scheduling. Automation in Construction, 14(3), 393-404.
Zhang, C., Sun, J., Zhu, X., & Yang, Q. (2008). An improved particle swarm optimization algorithm for flowshop scheduling problem. Information Processing Letters, 108(4), 204-209.
Zhang, H., Li, X., Li, H., & Huang, F. (2005). Particle swarm optimization-based schemes for resource-constrained project scheduling. Automation in Construction, 14(3), 393-404.
Zeighamia, V., Akbarib, R., & Ziaratic, K. (2013). Development of a method based on particle swarm optimization to solve resource constrained project scheduling problem. Scientia Irancia, 20(6), 2123-2137.
Zheng, H. Y., Wang, L., & Wang, S. Y. (2014, July). A co-evolutionary teaching-learning-based optimization algorithm for stochastic RCPSP. InEvolutionary Computation (CEC), 2014 IEEE Congress on (pp. 587-594). IEEE.
Ziarati, K., Akbari, R., & Zeighami, V. (2011). On the performance of bee algorithms for resource-constrained project scheduling problem. Applied Soft Computing, 11(4), 3720-3733.
Akbari, R., Zeighami, V., & Ziarati, K. (2011). Artificial bee colony for resource constrained project scheduling problem. International Journal of Industrial Engineering Computations, 2(1), 45-60.
Akbari, R., Zeighami, V., & Akbari, I. (2012). An ABC-Genetic method to solve resource constrained project scheduling problem. Artificial Intelligence Research, 1(2), p185.
Alcaraz, J., & Maroto, C. (2001). A robust genetic algorithm for resource allocation in project scheduling. Annals of Operations Research, 102(1-4), 83-109.
Baar, T., Brucker, P., & Knust, S. (1999). Tabu search algorithms and lower bounds for the resource-constrained project scheduling problem (pp. 1-18). Springer US.
Bouleimen K. and Lecocq H.. (2003). A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research, 149(2), 268-281.
Chen, W., Shi, Y. J., Teng, H. F., Lan, X. P., & Hu, L. C. (2010). An efficient hybrid algorithm for resource-constrained project scheduling. Information Sciences, 180(6), 1031-1039.
Chen, R. M., Wu, C. L., Wang, C. M., & Lo, S. T. (2010). Using novel particle swarm optimization scheme to solve resource-constrained scheduling problem in PSPLIB. Expert systems with applications, 37(3), 1899-1910.
Civicioglu, P. (2012). Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm. Computers & Geosciences,46, 229-247.
Coelho, J., & Vanhoucke, M. (2011). Multi-mode resource-constrained project scheduling using RCPSP and SAT solvers. European Journal of Operational Research, 213(1), 73-82.
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(10), 1365-1384.
Fahmy, A., Hassan, T. M., & Bassioni, H. (2014). Improving RCPSP solutions quality with Stacking Justification–Application with particle swarm optimization. Expert Systems with Applications, 41(13), 5870-5881.
Hartmann, S., & Kolisch, R. (2000). Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem. European Journal of Operational Research, 127(2), 394-407.
Hartmann, S. (1998). A competitive genetic algorithm for resource?constrained project scheduling. Naval Research Logistics (NRL), 45(7), 733-750.
Hartmann, S. (2002). A self?adapting genetic algorithm for project scheduling under resource constraints. Naval Research Logistics (NRL), 49(5), 433-448.
Herbots, J., Herroelen, W., & Leus, R. (2004). Experimental investigation of the applicability of ant colony optimization algorithms for project scheduling. DTEW Research Report 0459, 1-25.
Jarboui, B., Damak, N., Siarry, P., & Rebai, A. (2008). A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems. Applied Mathematics and Computation, 195(1), 299-308.
Jia, Q., & Seo, Y. (2013). Solving resource-constrained project scheduling problems: conceptual validation of FLP formulation and efficient permutation-based ABC computation. Computers & Operations Research, 40(8), 2037-2050.
Jia, Q., & Seo, Y. (2013). An improved particle swarm optimization for the resource-constrained project scheduling problem. The International Journal of Advanced Manufacturing Technology, 67(9-12), 2627-2638.
Koulinas, G., Kotsikas, L., & Anagnostopoulos, K. (2014). A particle swarm optimization based hyper-heuristic algorithm for the classic resource constrained project scheduling problem. Information Sciences, 277, 680-693.
Kolisch, R. (1996). Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation. European Journal of Operational Research, 90(2), 320-333.
Kolisch, R., & Hartmann, S. (2006). Experimental investigation of heuristics for resource-constrained project scheduling: An update. European journal of operational research, 174(1), 23-37.
Kolisch, R., & Hartmann, S. (1999). Heuristic algorithms for the resource-constrained project scheduling problem: Classification and computational analysis (pp. 147-178). Springer US.
Kolisch, R., & Padman, R. (2001). An integrated survey of deterministic project scheduling. Omega, 29(3), 249-272.
Kumar, N. (2014). Study on meta-heuristics for resource constrained project scheduling problem. International Journal of Engineering, Management & Sciences, 1(2), 14-24.
Luo, X., Wang, D., Tang, J., & Tu, Y. (2006, June). An improved pso algorithm for resource-constrained project scheduling problem. In Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on (Vol. 1, pp. 3514-3518). IEEE.
Mendes, J. J. D. M., Gonçalves, J. F., & Resende, M. G. (2009). A random key based genetic algorithm for the resource constrained project scheduling problem. Computers & Operations Research, 36(1), 92-109.
Merkle, D., Middendorf, M., & Schmeck, H. (2002). Ant colony optimization for resource-constrained project scheduling. Evolutionary Computation, IEEE Transactions on, 6(4), 333-346.
Nasiri, M. M. (2013). A pseudo particle swarm optimization for the RCPSP. The International Journal of Advanced Manufacturing Technology, 65(5-8), 909-918.
Neumann, K., & Zimmermann, J. (1999). Methods for resource-constrained project scheduling with regular and nonregular objective functions and schedule-dependent time windows. In Project Scheduling (pp. 261-287). Springer US.
Nonobe, K., & Ibaraki, T. (2002). Formulation and tabu search algorithm for the resource constrained project scheduling problem. In Essays and surveys in metaheuristics (pp. 557-588). Springer US.
Orji, I. M., & Wei, S. (2013, April). Project scheduling under resource constraints: a recent survey. In International Journal of Engineering Research and Technology (Vol. 2, No. 2 (February-2013)). ESRSA Publications.
Ranjbar, M., Kianfar, F., & Shadrokh, S. (2008). Solving the resource availability cost problem in project scheduling by path relinking and genetic algorithm. Applied Mathematics and Computation, 196(2), 879-888.
Sanaei, P., Akbari, R., Zeighami, V., & Shams, S. (2013, January). Using firefly algorithm to solve resource constrained project scheduling problem. InProceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) (pp. 417-428). Springer India.
Schirmer, A. (2000). Case?based reasoning and improved adaptive search for project scheduling. Naval Research Logistics (NRL), 47(3), 201-222.
Shou, Y., Li, Y., & Lai, C. (2015). Hybrid particle swarm optimization for preemptive resource-constrained project scheduling. Neurocomputing, 148, 122-128.
Tseng, L. Y., & Chen, S. C. (2006). A hybrid metaheuristic for the resource-constrained project scheduling problem. European Journal of Operational Research, 175(2), 707-721.
Valls, V., Ballest??n, F., & Quintanilla, S. (2005). Justification and RCPSP: A technique that pays. European Journal of Operational Research, 165(2), 375-386.
Valls, V., Ballestin, F., & Quintanilla, S. (2008). A hybrid genetic algorithm for the resource-constrained project scheduling problem. European Journal of Operational Research, 185(2), 495-508.
Xiao, L., Tian, J., & Liu, Z. (2014, June). An Activity-List based Nested Partitions algorithm for Resource-Constrained Project Scheduling. In Intelligent Control and Automation (WCICA), 2014 11th World Congress on (pp. 3450-3454). IEEE.
Yang, B., Geunes, J., & O’brien, W. J. (2001). Resource-constrained project scheduling: Past work and new directions. Department of Industrial and Systems Engineering, University of Florida, Tech. Rep.
Zamani, R. (2013). A competitive magnet-based genetic algorithm for solving the resource-constrained project scheduling problem. European Journal of Operational Research, 229(2), 552-559.
Zhang, H., Li, X., Li, H., & Huang, F. (2005). Particle swarm optimization-based schemes for resource-constrained project scheduling. Automation in Construction, 14(3), 393-404.
Zhang, C., Sun, J., Zhu, X., & Yang, Q. (2008). An improved particle swarm optimization algorithm for flowshop scheduling problem. Information Processing Letters, 108(4), 204-209.
Zhang, H., Li, X., Li, H., & Huang, F. (2005). Particle swarm optimization-based schemes for resource-constrained project scheduling. Automation in Construction, 14(3), 393-404.
Zeighamia, V., Akbarib, R., & Ziaratic, K. (2013). Development of a method based on particle swarm optimization to solve resource constrained project scheduling problem. Scientia Irancia, 20(6), 2123-2137.
Zheng, H. Y., Wang, L., & Wang, S. Y. (2014, July). A co-evolutionary teaching-learning-based optimization algorithm for stochastic RCPSP. InEvolutionary Computation (CEC), 2014 IEEE Congress on (pp. 587-594). IEEE.
Ziarati, K., Akbari, R., & Zeighami, V. (2011). On the performance of bee algorithms for resource-constrained project scheduling problem. Applied Soft Computing, 11(4), 3720-3733.