An Evolutionary Algorithm Based on a Hybrid Multi-Attribute Decision Making Method for the Multi-Mode Multi-Skilled Resource-constrained Project Scheduling Problem

Subject Areas : International Business

Amir Hossein Hosseinian ¹ (Department of Industrial Engineering, Faculty of Engineering, Islamic Azad University, Tehran North Branch, Tehran, Iran)
Vahid Baradaran ² (Department of Industrial Engineering, Faculty of Engineering, Islamic Azad University, Tehran North Branch, Tehran, Iran)

Received: 2017-12-16 Accepted : 2018-12-16 Published : 2019-07-01

Keywords:

References:

Afruzi, E., Najafi, A.A., Roghanian, E., & Mazinani, M., (2014). A Multi-Objective Imperialist Competitive Algorithm for solving discrete time, cost and quality trade-off problems with mode-identity and resource-constrained situations, Computers & Operations Research, 50, 80-96.

Afshar-Nadjafi, B., Rahimi, A., & Karimi, H., (2012). An Exact Algorithm for the Mode Identity Project Scheduling Problem, Journal of Optimization in Industrial Engineering, 10, 55-63.

Agarwal, A., Colak, S., & Erenguc, S., (2011). A Neurogenetic approach for the resource-constrained project scheduling problem, Computers & Operations Research, 38, 44-50.

Agarwal, A., Colak, S., & Erenguc, S., (2015). Metaheuristic Methods, in: Schwindt, C., Zimmermann, J., (Eds.), Handbook on Project Management and Scheduling Vol.1, Springer International Publishing. New York, 57-74.

Al-Anzi, F.S., Al-Zame, K., & Allahverdi, A., (2010). Weighted Multi-Skill Resources Project Scheduling, Journal of Software Engineering & Applications, 3(12), 1125-1130.

Almeida, B.F., Correia, I., & Saldanha-da-Gama, F., (2016). Priority-based heuristics for the multi-skill resource constrained project scheduling problem, Expert Systems with Applications, 57(15), 91–103.

Azaron, A., Katagiri, H., Sakawa, M., Kato, K., & Memariani, A., (2006). A multi-objective resource allocation problem in PERT networks. European Journal of Operational Research, 172(3), 838-854.

Bellenguez, O., & Néron, E., (2005). Lower Bounds for the Multi-skill Project Scheduling Problem with Hierarchical Levels of Skills, Practice and Theory of Automated Timetabling V, 3616, 229-243.

Bellenguez, O., & Néron, E., (2007). A branch-and-bound method for solving multi-skill project scheduling problem, Rairo Operations Research, 41, 155-170.

Blazewicz, J., Lenstra, J.K. & Kan, A., (1983). Scheduling subject to resource constraints: Classification and complexity, Discrete Applied Mathematics, 5(1), 11-24.

Bouleimen, K., & 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, R., Liang, C., Gu, D., and Leung, J., (2017). A multi-objective model for multi-project scheduling and multi-skilled staff assignment for IT product development considering competency evolution, International Journal of Production Research, 55(21), 1-29.

Cordeau, J., Laporte, G., Pasin, F., & Ropke, S., (2010). Scheduling Technicians and Tasks in a Telecommunications Company, Journal of Scheduling, 13(4), 393-409.

Corominas, A., Ojeda, J., & Pastor, R., (2005). Multi-objective allocation of multi-function workers with lower bounded capacity, Journal of the Operational Research Society, 56(6), 738-743.

Correia, I., & Saldanha-da-Gama, F., (2014). The impact of fixed and variable costs in a multi-skill project scheduling problem: An empirical study, Computers & Industrial Engineering, 72, 230-238.

Deb K., Pratap, A., Agrawal S., & Meyarivan, T., (2002). A Fast and Elitist Multi-objective Genetic Algorithm: NSGA-II, IEEE transactions on evolutionary computation, 6(2), 182-197.

Firat, M., & Hurkens, C.A.J., (2012). An improved MIP-based approach for a multi-skill workforce scheduling problem, Journal of Scheduling, 15(3), 363-380.

Gao, J., Chen, R., & Deng, W., (2013). An efficient tabu search algorithm for the distributed permutation flowshop scheduling problem, International Journal of Production Research, 51(3), 641-651.

Gomar, J., Haas, C., & Morton, D., (2002). Assignment and Allocation Optimization of Partially Multiskilled Workforce, Journal of construction engineering and management, 128(2), 103-109.

Gutjahr, W.J., Katzensteiner, S., Reiter, P., Stummer, C., & Denk, M., (2008). Competence-driven project portfolio selection, scheduling and staff assignment, Central European Journal of Operations Research, 16(3), 281-306.

Gutjahr, W. J., Katzensteiner, S., Reiter, P., Stummer, C., & Denk, M., (2010). Multi-objective decision analysis for competence-oriented project portfolio selection, European Journal of Operational Research, 205(3), 670-679.

Hassanpour, J., Ghodoosi, M., & Hosseini, Z.S., (2017). Optimizing a Bi-objective Preemptive Multi-mode Resource-Constrained Project Scheduling Problem: NSGA-II and MOICA Algorithms, Journal of Optimization in Industrial Engineering, 21, 79-91.

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, 394-407.

Hegazy, T., Shabeeb, K., Elbeltagi, E., & Cheema, T., (2000). Algorithm for scheduling with multiskilled constrained resources, Journal of construction engineering and management, 126(6), 414-421.

Hermerl, C., & Kolisch, R., (2010). Scheduling and staffing multiple projects with a multi-skilled workforce, OR Spectrum, 32, 343-368.

Hosseini, Z.S., Hassanpour, J., & Roghanian, E., (2014). A Bi-objective Pre-emption Multi-mode Resource Constrained Project Scheduling Problem with due Dates in the Activities, Journal of Optimization in Industrial Engineering, 15, 15-25.

Javanmard, S., Nadjafi, B., & Niaki, S.T.A., (2016). Preemptive multi-skilled resource investment project scheduling problem; mathematical modelling and solution approaches, Computers and Chemical Engineering, 96(1), 55-68.

Kadrou, Y., & Najid, N.M., (2006). Tabu Search Algorithm for the MRCPSP with Multi-Skilled Labor, in: Proc. Comput. Eng. Syst. Appl., IMACS Multi-conference, 1302-1309.

Kazemipoor, H., Tavakkoli-Moghaddam, R., Shahnazari-Shahrezaei, P., & Azaron, A., (2013). A differential evolution algorithm to solve multi-skilled project portfolio scheduling problems, The International Journal of Advanced Manufacturing Technology, 64(5-8), 1099-1111.

Kazemipoor, H., Tavvakoli-Moghaddam, E., & Sharezaei, P., (2013). Solving a novel multi-skilled project scheduling model by scatter search, South African Journal of Industrial Engineering, 24(1), 121-135.

Li, H., & Womer, K., (2009). A Decomposition Approach for Shipboard Manpower Scheduling, Military Operations Research, 14, 1-25.

Li, W., & Womer, K., (2009). Scheduling projects with multi-skilled personnel by a hybrid MILP/CP benders decomposition algorithm, Journal of Scheduling, 12, 281-298.

Lotfi, F.H., & Fallahnejad, R., (2010). Imprecise Shannon’s Entropy and Multi Attribute Decision Making, Entropy, 12, 53-62.

Maghsoudlou, H.M., Nadjafi, B., & Niaki, S.T.A., (2016). A multi-objective invasive weeds optimization algorithm for solving multi-skill multi-mode resource constrained project scheduling problem, Computers and Chemical Engineering, 8(1), 157-169.

Maghsoudlou, H.M., Nadjafi, B., & Niaki, S.T.A., 2017. Multi-skilled project scheduling with level-dependent rework risk; three multi-objective mechanisms based on cuckoo search, Applied Soft Computing, 54, 46-61.

Mehmanchi, E., & Shadrokh, S., (2013). Solving a New Mixed Integer Non-Linear Programming Model of the Multi-Skilled Project Scheduling Problem Considering Learning and Forgetting Effect, Proceedings of the 2013 IEEE IEEM, Bangkok, Thailand.

Mehdizadeh, E., & Kivi, A.F., (2014). Three Metaheuristic Algorithms for Solving the Multi-item Capacitated Lot-sizing Problem with Product Returns and Remanufacturing, Journal of Optimization in Industrial Engineering, 16, 41-53.

Miller, B., & Goldberg, D.E., (1996). Genetic algorithms, selection schemes, and the varying effects of noise, Evolutionary Computation, 4(2), 113-131.

Montoya, C., Bellenguez-Morineau, O., Pinson, E., & Rivera. D., (2014). Branch-and-price approach for the multi-skill project scheduling problem, Optimization Letters, 8(5), 1721-1734.

Myszkowski, P.B, & Skowronski, M., (2013). Specialized genetic operators for multi skill resource-constrained project scheduling problem, 19th International Conference on Soft Computing MENDEL, 57-62.

Myszkowski, P.B., Skowronski, M., & Podlodowski, L., (2013). Novel heuristic solutions for Multi–Skill Resource–Constrained Project Scheduling Problem, Proceedings of the 2013 Federated Conference on Computer Science and Information Systems, 159-166.

Myszkowski, P.B., Skowronski, M., Olech, L.P., & Oslizlo, K., (2015). Hybrid ant colony optimization in solving multi-skill resource-constrained project scheduling problem, Soft Computing, 19(12), 3599-3619.

Nader, B., (2013). The Project Portfolio Selection and Scheduling Problem: Mathematical Model and Algorithms, Journal of Optimization in Industrial Engineering, 13, 65-72.

Najafi, A.A., & Salimi, M., (2018). Modeling and Solution Procedure for a Preemptive Multi-Objective Multi-Mode Project Scheduling Model in Resource Investment Problems, Journal of Optimization in Industrial Engineering, 11(1), 181-190.

Opricovic, S., & Tzeng, G. H., (2004). Compromise Solution by MCDM Methods: A comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research, 156, 445-455.

Opricovic, S., & Tzeng, G. H., (2007). Extended VIKOR method in comparison with outranking methods, European Journal of Operational Research, 178, 514–529.

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, 879-888.

Tabrizi, B.H., Tavvakoli-Moghaddam, R., & Ghaderi, S.F., (2014). A two-phase method for a multi-skilled project scheduling problem with discounted cash flows, Scientia Iranica, 21(3), 1083-1095.

Valls, V., Perez, A., & Quintanilla, S., (2009). Skilled workforce scheduling in Service Centers, European Journal of Operational Research, 193(3), 791-804.

Walter, M., & Zimmermann, J., (2016). Minimizing average project team size given multi-skilled workers with heterogeneous skill levels. Computers & Operations Research, 70, 163–179.

Wu, M., & Sun, S., (2006). A project scheduling and staff assignment model considering learning effect, The International Journal of Advanced Manufacturing Technology, 28(11), 1190-1195.

Yaghoubi, S., Noori, S., Azaron, A., & Tavakkoli-Moghaddam, R., (2011). Resource allocation in dynamic PERT networks with finite capacity, European Journal of Operational Research, 215(3), 670-678.

Yaghoubi, S., Noori, S., Azaron, A., & Fynes, B., (2015). Resource allocation in multi-class dynamic PERT networks with finite capacity, European Journal of Operational Research, 247(3), 879-894.

Zheng, H., Wang, L., & Zheng, X., (2015). Teaching–learning-based optimization algorithm for multiskill resource constrained project scheduling problem, Soft Computing, 21(6), 1537-1548.