A new combination of multi-mode resource-constrained project scheduling and group decision-making process with interval-fuzzy information

Document Type: Research Paper

Authors

Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran

Abstract

Multi-mode resource-constrained project scheduling problem (MRCPSP) is one of the most important extensions of the basic RCPSP. In this paper, a new mathematical model for MRCPSP is presented with a time-quality trade-off approach. The model has two objectives, the first objective minimizes the project completion time, and the second objective maximizes the project quality while the quality of activities can be increased based on the reworking. In addition, in the presented model, total available resources, including renewable and non-renewable, are decision variables. The quality and duration of project activities are interval forms. For this purpose, a new expert weighting method based on interval information is presented to unify the experts’ views. The group decision-making method applies a bi-directional projection measure to the positive ideal solution and two negative ideal solutions. Moreover, a new extended interval-fuzzy solution method based on goal programming is proposed to deal with the interval information and mathematical model objectives. The presented mathematical model and group decision-making method are solved with a dataset, and some sensitivity analyses are reported.

Keywords

Main Subjects


Arditi, D., & Pattanakitchamroon, T. (2006). Selecting a delay analysis method in resolving construction claims. International Journal of project management, 24(2), 145-155.

Babu, A. J. G., & Suresh, N. (1996). Project management with time, cost, and quality considerations. European journal of operational research, 88(2), 320-327.

Baudry, G., Macharis, C., & Vallee, T. (2018). Range-based Multi-Actor Multi-Criteria Analysis: A combined method of Multi-Actor Multi-Criteria Analysis and Monte Carlo simulation to support participatory decision making under uncertainty. European Journal of Operational Research, 264(1), 257-269.

Birjandi, A., & Mousavi, S. M. (2019). Fuzzy resource-constrained project scheduling with multiple routes: A heuristic solution. Automation in Construction100, 84-102.‏

Birjandi, A., Mousavi, S. M., Hajirezaie, M., & Vahdani, B. (2019). Optimizing and Solving Project Scheduling Problem for Flexible Networks with Multiple Routes in Production Environments. Journal of Quality Engineering and Production Optimization, 4(1), 175-196.

Bodily, S. E. (1979). Note—A delegation process for combining individual utility functions. Management Science25(10), 1035-1041.‏

Bruni, M. E., Beraldi, P., Guerriero, F., & Pinto, E. (2011). A heuristic approach for resource constrained project scheduling with uncertain activity durations. Computers & Operations Research38(9), 1305-1318.‏

Chen, T. Y. (2015). The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making. Applied Soft Computing, 26, 57-73.

Chen, T. Y. (2016). An interval-valued intuitionistic fuzzy permutation method with likelihood-based preference functions and its application to multiple criteria decision analysis. Applied Soft Computing42, 390-409.

Cheng, M. Y., Tran, D. H., & Cao, M. T. (2016). Chaotic initialized multiple objective differential evolution with adaptive mutation strategy (CA-MODE) for construction project time-cost-quality trade-off. Journal of Civil Engineering and Management22(2), 210-223.‏

Chung, C. K., Chen, H. M., Chang, C. T., & Huang, H. L. (2018). On fuzzy multiple objective linear programming problems. Expert Systems with Applications, 114, 552-562. ‏

Das, S., & Kar, S. (2014). Group decision making in medical system: An intuitionistic fuzzy soft set approach. Applied soft computing, 24, 196-211.

Deli, I. (2015). npn-Soft sets theory and their applications. Ann Fuzzy Math Inform, 10(6), 847-862.

Dey, B., Bairagi, B., Sarkar, B., & Sanyal, S. K. (2017). Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain. Computers & Industrial Engineering, 105, 101-122.

Dorfeshan, Y., & Mousavi, S. M. (2019). A group TOPSIS-COPRAS methodology with Pythagorean fuzzy sets considering weights of experts for project critical path problem. Journal of Intelligent & Fuzzy Systems, 36(2), 1375-1387.

Dorfeshan, Y., Tavakkoli-Moghaddam, R., Mousavi, S. M., & Vahedi-Nouri, B. (2020). A new weighted distance-based approximation methodology for flow shop scheduling group decisions under the interval-valued fuzzy processing time. Applied Soft Computing, 106248.

Haghighi, M. H., Mousavi, S. M., Antuchevičienė, J., & Mohagheghi, V. (2019). A new analytical methodology to handle time-cost trade-off problem with considering quality loss cost under interval-valued fuzzy uncertainty. Technological and Economic Development of Economy, 25(2), 277-299.

Hancerliogullari, G., Hancerliogullari, K. O., & Koksalmis, E. (2017). The use of multi-criteria decision making models in evaluating anesthesia method options in circumcision surgery. BMC medical informatics and decision making, 17(1), 14.

Hazır, Ö., Erel, E., & Günalay, Y. (2011). Robust optimization models for the discrete time/cost trade-off problem. International Journal of Production Economics, 130(1), 87-95.

Hegazy, T., Said, M., & Kassab, M. (2011). Incorporating rework into construction schedule analysis. Automation in construction, 20(8), 1051-1059.

Hwang, B. G., Thomas, S. R., Haas, C. T., & Caldas, C. H. (2009). Measuring the impact of rework on construction cost performance. Journal of construction engineering and management, 135(3), 187-198.

Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making (pp. 58-191). Springer, Berlin, Heidelberg.

Icmeli-Tukel, O., & Rom, W. O. (1997). Ensuring quality in resource constrained project scheduling. European journal of operational research, 103(3), 483-496.

Kolisch, R., & Sprecher, A. (1997). PSPLIB-a project scheduling problem library: OR software-ORSEP operations research software exchange program. European journal of operational research, 96(1), 205-216.

Kolisch, R., Sprecher, A., & Drexl, A. (1995). Characterization and generation of a general class of resource-constrained project scheduling problems. Management science, 41(10), 1693-1703.

Konak, A., Coit, D. W., & Smith, A. E. (2006). Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering & System Safety, 91(9), 992-1007. ‏

Liao, H., Li, Z., Zeng, X. J., & Liu, W. (2017). A comparison of distinct consensus measures for group decision making with intuitionistic fuzzy preference relations. International Journal of Computational Intelligence Systems, 10(1), 456-469.

Liu, P. (2017). Multiple attribute group decision making method based on interval-valued intuitionistic fuzzy power Heronian aggregation operators. Computers & Industrial Engineering108, 199-212. ‏

Liu, W. (2016). VIKOR method for group decision making problems with ordinal interval numbers'. International Journal of Hybrid Information Technology, 9(2), 67-74. ‏

Liu, Y., Dong, Y., Liang, H., Chiclana, F., & Herrera-Viedma, E. (2018). Multiple attribute strategic weight manipulation with minimum cost in a group decision making context with interval attribute weights information. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(10), 1981-1992. ‏

Moghiseh, H., Mousavi, S. M., & Patoghi, A. (2019). A new project controlling approach based on earned value management and group decision-making process with triangular intuitionistic fuzzy sets. Journal of Industrial and Systems Engineering, 12(3), 177-195.

Mohagheghi, V., & Mousavi, S. M. (2019). A new framework for high-technology project evaluation and project portfolio selection based on Pythagorean fuzzy WASPAS, MOORA and mathematical modeling. Iranian Journal of Fuzzy Systems, 16(6), 89-106.

Mohagheghi, V., Mousavi, S. M., Antuchevičienė, J., & Dorfeshan, Y. (2019). Sustainable infrastructure project selection by a new group decision-making framework introducing MORAS method in an interval type 2 fuzzy environment. International Journal of Strategic Property Management, 23(6), 390-404.

Muritiba, A. E. F., Rodrigues, C. D., & da Costa, F. A. (2018). A Path-Relinking algorithm for the multi-mode resource-constrained project scheduling problem. Computers & Operations Research, 92, 145-154.

Nguyen, H. (2016). A new interval-valued knowledge measure for interval-valued intuitionistic fuzzy sets and application in decision making. Expert Systems with Applications56, 143-155.

Peng, X., & Liu, C. (2017). Algorithms for neutrosophic soft decision making based on EDAS, new similarity measure and level soft set. Journal of Intelligent & Fuzzy Systems, 32(1), 955-968.

Sonmez, R., & Bettemir, Ö. H. (2012). A hybrid genetic algorithm for the discrete time–cost trade-off problem. Expert Systems with Applications, 39(13), 11428-11434.

Tareghian, H. R., & Taheri, S. H. (2006). On the discrete time, cost and quality trade-off problem. Applied mathematics and computation, 181(2), 1305-1312.

Tian, Z. P., Zhang, H. Y., Wang, J., Wang, J. Q., & Chen, X. H. (2016). Multi-criteria decision-making method based on a cross-entropy with interval neutrosophic sets. International Journal of Systems Science, 47(15), 3598-3608.

Tsao, C. Y., & Chen, T. Y. (2016). A projection-based compromising method for multiple criteria decision analysis with interval-valued intuitionistic fuzzy information. Applied Soft Computing45, 207-223.

Turner, J. R., & Keegan, A. (1999). The versatile project-based organization: governance and operational control. European management journal, 17(3), 296-309.

Wang, G. A., Jiao, J., Abrahams, A. S., Fan, W., & Zhang, Z. (2013). ExpertRank: A topic-aware expert finding algorithm for online knowledge communities. Decision support systems54(3), 1442-1451. ‏

Wang, L., & Fang, C. (2012). An effective estimation of distribution algorithm for the multi-mode resource-constrained project scheduling problem. Computers & Operations Research39(2), 449-460. ‏

Wang, Z. J., & Li, K. W. (2012). An interval-valued intuitionistic fuzzy multiattribute group decision making framework with incomplete preference over alternatives. Expert Systems with Applications39(18), 13509-13516.

Weglarz, J., Józefowska, J., Mika, M., & Waligóra, G. (2011). Project scheduling with
finite or infinite number of activity processing modes – A survey. European Journal of Operational Research, 208, 177–205.

Wei, G., Lin, R., Zhao, X., & Wang, H. (2014). An approach to multiple attribute decision making based on the induced Choquet integral with fuzzy number intuitionistic fuzzy information. Journal of Business Economics and Management15(2), 277-298. ‏

Wuliang, P., & Chengen, W. (2009). A multi-mode resource-constrained discrete time–cost trade-off problem and its genetic algorithm based solution. International journal of project management, 27(6), 600-609.

Xu, J., Zheng, H., Zeng, Z., Wu, S., & Shen, M. (2012). Discrete time–cost–environment trade-off problem for large-scale construction systems with multiple modes under fuzzy uncertainty and its application to Jinping-II Hydroelectric Project. International Journal of Project Management, 30(8), 950-966.

Xu, Z., & Da, Q. (2004). Projection method for uncertain multi-attribute decision making with preference information on alternatives. International Journal of Information Technology & Decision Making3(03), 429-434.

Xu, Z., & Hu, H. (2010). Projection models for intuitionistic fuzzy multiple attribute decision making. International Journal of Information Technology & Decision Making9(02), 267-280.

Yang, Q., & Du, P. A. (2015). A straightforward approach for determining the weights of decision makers based on angle cosine and projection method. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 9(10), 3127-3133.

Yang, Q., Du, P. A., Wang, Y., & Liang, B. (2018). Developing a rough set based approach for group decision making based on determining weights of decision makers with interval numbers. Operational Research, 18(3), 757-779. ‏

Yu, G. F., Li, D. F., & Fei, W. (2018). A novel method for heterogeneous multi-attribute group decision making with preference deviation. Computers & Industrial Engineering, 124, 58-64. ‏

Yue Z (2014) TOPSIS-based group decision-making methodology in intuitionistic fuzzy setting. Inf Sci 277:141–153

Yue, C. (2016). A geometric approach for ranking interval-valued intuitionistic fuzzy numbers with an application to group decision-making. Computers & Industrial Engineering102, 233-245.

Yue, C. (2018). A novel approach to interval comparison and application to software quality evaluation. Journal of Experimental & Theoretical Artificial Intelligence, 30(5), 583-602.

Yue, C. (2018). Normalized projection approach to group decision-making with hybrid decision information. International Journal of Machine Learning and Cybernetics, 9(8), 1365-1375. ‏

Yue, C. (2019). An interval-valued intuitionistic fuzzy projection-based approach and application to evaluating knowledge transfer effectiveness. Neural Computing and Applications, 31(11), 7685-7706.‏

Yue, Z. (2011). Deriving decision maker’s weights based on distance measure for interval-valued intuitionistic fuzzy group decision making. Expert Systems with Applications38(9), 11665-11670. ‏

Yue, Z. (2012). Developing a straightforward approach for group decision making based on determining weights of decision makers. Applied Mathematical Modelling36(9), 4106-4117. ‏

Yue, Z. (2013). An intuitionistic fuzzy projection-based approach for partner selection. Applied Mathematical Modelling37(23), 9538-9551. ‏

Yue, Z. (2014). TOPSIS-based group decision-making methodology in intuitionistic fuzzy setting. Information Sciences, 277, 141-153.

Yue, Z., & Jia, Y. (2015). A group decision making model with hybrid intuitionistic fuzzy information. Computers & Industrial Engineering, 87, 202-212.

Yue, Z., & Jia, Y. (2017). A direct projection-based group decision-making methodology with crisp values and interval data. Soft Computing, 21(9), 2395-2405.

Zavadskas, E. K., Bausys, R., Kaklauskas, A., Ubarte, I., Kuzminske, A., & Gudiene, N. (2017). Sustainable market valuation of buildings by the single-valued neutrosophic MAMVA method. Applied Soft Computing, 57, 74-87.

Zhang, X., Jin, F., & Liu, P. (2013). A grey relational projection method for multi-attribute decision making based on intuitionistic trapezoidal fuzzy number. Applied Mathematical Modelling37(5), 3467-3477.