How to cite this paper
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.
Refrences
Abbasi, B., Shadrokh, S., & Arkat, J.(2006). Bi-objective resource-constrained project scheduling with robustness and makespan criteria. Journal of Applied Mathematics and Computation, 180, 146–152.
Agarwal, A., Colak, S., & Erenguc, S.(2010). A Neurogenetic approach for the resource-constrained project scheduling problem. Computers & Operations Research, doi:10.1016/j.cor.2010.01.007.
Akbari, R., Mohammadi, M., & Ziarati, K.(2010). A novel bee swarm optimization algorithm for numerical function optimization. Journal of Communications on Nonlinear Sciences and Numerical Simulation, 15, 3142-3155.
Ashtiani, B., Leus, R., & Aryanezhad, M. B.(2009). New competitive results for the stochastic resource-constrained project scheduling problem: exploring the benefits of pre-processing. Journal of Scheduling, doi: 10.1007/s10951-009-0143-7.
Alatas B.(2010). Chaotic bee colony algorithms for global numerical optimization. Expert Systems with Applications, 37, 5682-5687.
Blazewicz J., Lenstra J. K., & Rinnooy Kan A. H. G.(1983). Scheduling projects to resource constraints: classification and complexity. Discrete Applied Mathematics, 5, 11–24.
Boctor, F. F.(1990). Some efficient multi-heuristic procedures for resourceconstrained project scheduling. European Journal of Operational Research, 49, 3–13.
Boctor, F. F.(1996). An adaptation of the simulated annealing algorithm for solving resource-constrained project scheduling problems. International Journal of Production Research, 34, 2335–2351.
Bouleimen, K., & Lecocq, H.(1993). A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research, 149, 268–281.
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, 1899–1910.
Chen, R. M., Lo, S. T., Wang, C. J., & Wu, C. L.(2006). Multiprocessor system scheduling with precedence and resources constraints by ant colony system. Proceeding of ICS Conference, 292-297.
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, 1899–1910.
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, 1031–1039.
Damak, N., Jarboui, B., Siarry, P., & Loukil, T.(2009). Differential evolution for solving multi-mode resource-constrained project scheduling problems. Computers & Operations Research, 36, 2653 – 2659.
Debels, D., & Vanhoucke, M.(2004). An Electromagnetism Meta-Heuristic For The Resource-Constrained Project Scheduling Problem. Lecture Notes on Computer Science, 3871, 259-270.
Debels, D., De Reyck, B., Leus, R., & Vanhoucke M.(2006). A hybrid scatter search /Electromagnetism meta–heuristic for project scheduling. European Journal of Operational Research, 169, 638-653.
Fekete, S. P., & Schepers, J.(1998). New classes of lower bounds for bin-packing problems. Lecture Notes in Computer Science, 1412, 257–270.
Karaboga, D., & Basturk, B.(2007). A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. Journal of Global Optimization, 39, 459–471.
Karaboga, D., & Akay, B.(2009). A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation, 214, 108-132.
Kolisch, R., & Hartmann, S.(1999). Heuristic algorithms for solving the resource-constrained project scheduling problem: classification and computational analysis. J. Weglarz (Ed.), Project Scheduling: Recent Models, algorithms and Applications, Kluwer Academic Publishers, Berlin, 147–178.
Kolisch, R.(1996). Efficient priority rules for the resource-constrained project scheduling problem. Journal of Operations Management, 14, 179–192.
Krüger, D., & Scholl, A.(2009). A heuristic solution framework for the resource constrained multi-project scheduling problem with sequence-dependent transfer times. European Journal of Operational Research, 197, 492–508.
Hartmann, S., & Briskorn, D.(2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of Operational Research, 207, 1-14.
Hartmann, S.(1998). A competitive genetic algorithm for resourceconstrained project scheduling. Naval Research Logistics, 45, 733– 750.
Mahdi Mobini, M. D., Rabbani, M., Amalnik, M. S., Razmi, J., & Rahimi-Vahed, A. R.(2009). Using an enhanced scatter search algorithm for a resource-constrained project scheduling problem. Soft Computing, 13, 597–610.
Mendes, J. J., Gonalves, J. F., & Resende M.G.C.(2009). A random key based genetic algorithm for the resource constrained project scheduling problem. Computers & Operations Research, 36, 92–109.
Mendes, J. J., Gonalves, J. F., Resende, M. G. C.(2009). A random key based genetic algorithm for the resource constrained project scheduling problem. Computers & Operations Research, 36, 92–109.
Mingozzi, A., Maniezzo, V., Ricciardelli, S., & Bianco, L.(1998). An exact algorithm for project scheduling with resource constraints based on a new mathematical formulation. Journal of Management Science, 44, 714–729.
Mobini, M., Mobini Z., & Rabbani M.(2010). An Artificial Immune Algorithm for the project scheduling problem under resource constraints. Applied Soft Computing, doi:10.1016/j.asoc.2010.06.013.
Montoya-Torres, J. R., Gutierrez-Franco, E., & Pirachica N-Mayorga, C.(2010). Project scheduling with limited resources using a genetic algorithm. International Journal of Project Management, 28, 619–628.
Neumann, K., Schwindt, C., & Zimmermann, J.(2003). Order-based neighborhoods for project scheduling with nonregular objective functions. European Journal of Operational Research, 149, 2, 325-343.
Pan, Q. K., M. Tasgetiren F., Suganthan, P. N., & Chua, T. J.(2010) A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem, Information Sciences. doi:10.1016/j.ins.2009.12.025.
Pham, D. T., Castellani, M., & Fahmy, A. A.(2008). Learning the inverse kinematics of a Robot manipulator using the bees algorithm. IEEE international conference on industrial informatics, 493–498.
Rabbani, M., Fatemi Ghomi, S.M.T., Jolai, F., & Lahiji, N.S.(2007). A new heuristic for resource-constrained project scheduling in stochastic networks using critical chain concept. European Journal of Operational Research, 176, 794–808.
Ranjbar, M.(2008). Solving the resource-constrained project scheduling problem using filter-and-fan approach. Journal of Applied Mathematics and Computation, 201, 313–318.
Sprecher, A.(2000). Scheduling resource-constrained projects competitively at modest memory requirements. Management Science, 46, 710–723.
Stork, F., & Uetz, M.(2005). On the generation of circuits and minimal forbidden sets. Mathematical Programming, 102, 185–203.
Teodorovic, D., & Dell Orco, M.(2007). Bee colony optimization–a cooperative learning approach to complex transportation problems. Advanced OR and AI Methods in Transportation, 51–60.
Teodorovic, D., Panta, L., Goran M., & Dell, O. M.(2006). Bee colony optimization: principles and applications. Proceeding of eighth seminar on neural network applications in electrical engineering, Neurel, 151–156.
Thomas, P., R., & Salhi S.(1998). A tabu search approach for the resource constrained project scheduling problem. Journal of Heuristics, 4, 123–139.
Tormos, P., & Lova, A.(2001). A competitive heuristic solution technique for resource-constrained project scheduling. Annals of Operations Research, 102, 65–81.
Tseng, L.Y., & Chen, S. C.(2006). A hybrid metaheuristic for the resource-constrained project scheduling problem, European Journal of Operational Research, 175, 707–721.
Valls V., Ballestın F., & Quintanilla, S.(2008). A hybrid genetic algorithm for the resource-constrained project scheduling problem. European Journal of Operational Research, 185, 495–508.
Zhang, H., Li, X., Li, H., & Huang, F.(2005). Particle swarm optimization-based schemes for resource-constrained project scheduling. Journal of Automation in Construction, 14, 393– 404.
Zhang, H., Li, H., & Tam, C. M.(2006). Particle swarm optimization for resource-constrained project scheduling, International Journal of Project Management, 24, 83–92.
Agarwal, A., Colak, S., & Erenguc, S.(2010). A Neurogenetic approach for the resource-constrained project scheduling problem. Computers & Operations Research, doi:10.1016/j.cor.2010.01.007.
Akbari, R., Mohammadi, M., & Ziarati, K.(2010). A novel bee swarm optimization algorithm for numerical function optimization. Journal of Communications on Nonlinear Sciences and Numerical Simulation, 15, 3142-3155.
Ashtiani, B., Leus, R., & Aryanezhad, M. B.(2009). New competitive results for the stochastic resource-constrained project scheduling problem: exploring the benefits of pre-processing. Journal of Scheduling, doi: 10.1007/s10951-009-0143-7.
Alatas B.(2010). Chaotic bee colony algorithms for global numerical optimization. Expert Systems with Applications, 37, 5682-5687.
Blazewicz J., Lenstra J. K., & Rinnooy Kan A. H. G.(1983). Scheduling projects to resource constraints: classification and complexity. Discrete Applied Mathematics, 5, 11–24.
Boctor, F. F.(1990). Some efficient multi-heuristic procedures for resourceconstrained project scheduling. European Journal of Operational Research, 49, 3–13.
Boctor, F. F.(1996). An adaptation of the simulated annealing algorithm for solving resource-constrained project scheduling problems. International Journal of Production Research, 34, 2335–2351.
Bouleimen, K., & Lecocq, H.(1993). A new efficient simulated annealing algorithm for the resource-constrained project scheduling problem and its multiple mode version. European Journal of Operational Research, 149, 268–281.
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, 1899–1910.
Chen, R. M., Lo, S. T., Wang, C. J., & Wu, C. L.(2006). Multiprocessor system scheduling with precedence and resources constraints by ant colony system. Proceeding of ICS Conference, 292-297.
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, 1899–1910.
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, 1031–1039.
Damak, N., Jarboui, B., Siarry, P., & Loukil, T.(2009). Differential evolution for solving multi-mode resource-constrained project scheduling problems. Computers & Operations Research, 36, 2653 – 2659.
Debels, D., & Vanhoucke, M.(2004). An Electromagnetism Meta-Heuristic For The Resource-Constrained Project Scheduling Problem. Lecture Notes on Computer Science, 3871, 259-270.
Debels, D., De Reyck, B., Leus, R., & Vanhoucke M.(2006). A hybrid scatter search /Electromagnetism meta–heuristic for project scheduling. European Journal of Operational Research, 169, 638-653.
Fekete, S. P., & Schepers, J.(1998). New classes of lower bounds for bin-packing problems. Lecture Notes in Computer Science, 1412, 257–270.
Karaboga, D., & Basturk, B.(2007). A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. Journal of Global Optimization, 39, 459–471.
Karaboga, D., & Akay, B.(2009). A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation, 214, 108-132.
Kolisch, R., & Hartmann, S.(1999). Heuristic algorithms for solving the resource-constrained project scheduling problem: classification and computational analysis. J. Weglarz (Ed.), Project Scheduling: Recent Models, algorithms and Applications, Kluwer Academic Publishers, Berlin, 147–178.
Kolisch, R.(1996). Efficient priority rules for the resource-constrained project scheduling problem. Journal of Operations Management, 14, 179–192.
Krüger, D., & Scholl, A.(2009). A heuristic solution framework for the resource constrained multi-project scheduling problem with sequence-dependent transfer times. European Journal of Operational Research, 197, 492–508.
Hartmann, S., & Briskorn, D.(2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of Operational Research, 207, 1-14.
Hartmann, S.(1998). A competitive genetic algorithm for resourceconstrained project scheduling. Naval Research Logistics, 45, 733– 750.
Mahdi Mobini, M. D., Rabbani, M., Amalnik, M. S., Razmi, J., & Rahimi-Vahed, A. R.(2009). Using an enhanced scatter search algorithm for a resource-constrained project scheduling problem. Soft Computing, 13, 597–610.
Mendes, J. J., Gonalves, J. F., & Resende M.G.C.(2009). A random key based genetic algorithm for the resource constrained project scheduling problem. Computers & Operations Research, 36, 92–109.
Mendes, J. J., Gonalves, J. F., Resende, M. G. C.(2009). A random key based genetic algorithm for the resource constrained project scheduling problem. Computers & Operations Research, 36, 92–109.
Mingozzi, A., Maniezzo, V., Ricciardelli, S., & Bianco, L.(1998). An exact algorithm for project scheduling with resource constraints based on a new mathematical formulation. Journal of Management Science, 44, 714–729.
Mobini, M., Mobini Z., & Rabbani M.(2010). An Artificial Immune Algorithm for the project scheduling problem under resource constraints. Applied Soft Computing, doi:10.1016/j.asoc.2010.06.013.
Montoya-Torres, J. R., Gutierrez-Franco, E., & Pirachica N-Mayorga, C.(2010). Project scheduling with limited resources using a genetic algorithm. International Journal of Project Management, 28, 619–628.
Neumann, K., Schwindt, C., & Zimmermann, J.(2003). Order-based neighborhoods for project scheduling with nonregular objective functions. European Journal of Operational Research, 149, 2, 325-343.
Pan, Q. K., M. Tasgetiren F., Suganthan, P. N., & Chua, T. J.(2010) A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem, Information Sciences. doi:10.1016/j.ins.2009.12.025.
Pham, D. T., Castellani, M., & Fahmy, A. A.(2008). Learning the inverse kinematics of a Robot manipulator using the bees algorithm. IEEE international conference on industrial informatics, 493–498.
Rabbani, M., Fatemi Ghomi, S.M.T., Jolai, F., & Lahiji, N.S.(2007). A new heuristic for resource-constrained project scheduling in stochastic networks using critical chain concept. European Journal of Operational Research, 176, 794–808.
Ranjbar, M.(2008). Solving the resource-constrained project scheduling problem using filter-and-fan approach. Journal of Applied Mathematics and Computation, 201, 313–318.
Sprecher, A.(2000). Scheduling resource-constrained projects competitively at modest memory requirements. Management Science, 46, 710–723.
Stork, F., & Uetz, M.(2005). On the generation of circuits and minimal forbidden sets. Mathematical Programming, 102, 185–203.
Teodorovic, D., & Dell Orco, M.(2007). Bee colony optimization–a cooperative learning approach to complex transportation problems. Advanced OR and AI Methods in Transportation, 51–60.
Teodorovic, D., Panta, L., Goran M., & Dell, O. M.(2006). Bee colony optimization: principles and applications. Proceeding of eighth seminar on neural network applications in electrical engineering, Neurel, 151–156.
Thomas, P., R., & Salhi S.(1998). A tabu search approach for the resource constrained project scheduling problem. Journal of Heuristics, 4, 123–139.
Tormos, P., & Lova, A.(2001). A competitive heuristic solution technique for resource-constrained project scheduling. Annals of Operations Research, 102, 65–81.
Tseng, L.Y., & Chen, S. C.(2006). A hybrid metaheuristic for the resource-constrained project scheduling problem, European Journal of Operational Research, 175, 707–721.
Valls V., Ballestın F., & Quintanilla, S.(2008). A hybrid genetic algorithm for the resource-constrained project scheduling problem. European Journal of Operational Research, 185, 495–508.
Zhang, H., Li, X., Li, H., & Huang, F.(2005). Particle swarm optimization-based schemes for resource-constrained project scheduling. Journal of Automation in Construction, 14, 393– 404.
Zhang, H., Li, H., & Tam, C. M.(2006). Particle swarm optimization for resource-constrained project scheduling, International Journal of Project Management, 24, 83–92.