A New Multi-objective Model for Multi-mode Project Planning with Risk

Authors

1 Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract

The purpose of this problem is to choose a set of project activities for crashing, in a way that the expected project time, cost and risk are minimized and the expected quality is maximized. In this problem, each project activity can be performed with a specific executive mode. Each executive mode is characterized with four measures, namely the expected time, cost, quality and risk. In this paper, linear relationships between time and cost, and between time and quality are omitted and the problem of the expected time-cost-quality tradeoff is considered in a probabilistic and discrete state. Then, to make the problem more real, the combination of four measures are considered as uncertain for each executive mode. It means that time, cost, quality or risk (or all of them) of each activity in each executive mode is considered as the expected numbers (probabilistic means). After modeling three objective problems, a test problem with nine activities is presented and solved by the NSGA-II algorithm. In order to improve the results and speed of the proposed algorithm in accessing Pareto solutions, a new hybrid algorithm, called MEM-NSGA, is presented that gives better solutions than the NSGA-II algorithm in the same conditions.

Keywords


1.     Guide, P., "A guide to the project management body of knowledge", in Project Management Institute. Vol. 3, (2004).

2.     Perera, S., "Linear programming solution to network compression", Journal of the Construction Division,  Vol. 106, No. 3, (1980), 315-326.

3.     Phillips Jr, S. and Dessouky, M.I., "Solving the project time/cost tradeoff problem using the minimal cut concept", Management Science,  Vol. 24, No. 4, (1977), 393-400.

4.     Deckro, R., Hebert, J. and Verdini, W., "Non-linear multiple criteria time/cost tradeoff", Proceedings of the 1987 Annual Western DSI, Palm Springs, CA,  (1987), 134-137.

5.     Patterson, J.H. and Huber, W.D., "A horizon-varying, zero-one approach to project scheduling", Management Science,  Vol. 20, No. 6, (1974), 990-998.

6.     Wiest, J.D. and Levy, F.K., "Management guide to pert/cpm",  Englewood Cliffs. Prentice-Hall, Inc, New Jersey, (1997).

7.     Babu, A. and Suresh, N., "Project management with time, cost, and quality considerations", European Journal of Operational Research,  Vol. 88, No. 2, (1996), 320-327.

8.     Tareghian, H.R. and Taheri, S.H., "On the discrete time, cost and quality trade-off problem", Applied Mathematics and Computation,  Vol. 181, No. 2, (2006), 1305-1312.

9.     Tareghian, H.R. and Taheri, S.H., "A solution procedure for the discrete time, cost and quality tradeoff problem using electromagnetic scatter search", Applied Mathematics and Computation,  Vol. 190, No. 2, (2007), 1136-1145.

10.   Li, H. and Love, P., "Using improved genetic algorithms to facilitate time-cost optimization", Journal of Construction Engineering and Management,  Vol. 123, No. 3, (1997), 233-237.

11.   Azaron, A. and Tavakkoli-Moghaddam, R., "Multi-objective time–cost trade-off in dynamic pert networks using an interactive approach", European Journal of Operational Research,  Vol. 180, No. 3, (2007), 1186-1200.

12.   Elazouni, A.M. and Metwally, F.G., "Expanding finance-based scheduling to devise overall-optimized project schedules", Journal of Construction Engineering and Management,  Vol. 133, No. 1, (2007), 86-90.

13.   Pathak, B.K. and Srivastava, S., "Moga-based time-cost tradeoffs: Responsiveness for project uncertainties", in Evolutionary Computation, 2007. CEC 2007. IEEE Congress on, IEEE., (2007), 3085-3092.

14.   Hooshyar, B., Tahmani, A. and Shenasa, M., "A genetic algorithm to time-cost trade off in project scheduling", in Evolutionary Computation, 2008. CEC 2008.(IEEE World Congress on Computational Intelligence). IEEE Congress on, IEEE., (2008), 3081-3086.

15.   Mohammadi, G., "Using genetic algorithms to solve industrial time-cost trade-off problems", Indian Journal of Science and Technology,  Vol. 4, No. 10, (2011), 1273-1278.

16.   B.K., P., Srivastava, S. and Srivastava, K., "Neural network embedded with multi-objective genetic algorithm to solve nonlinear time cost trade-off problem of project scheduling", Journal of Scientific and Industrial Research,  Vol. 67, (2008), 124-131.

17.   Iranmanesh, H., Skandari, M. and Allahverdiloo, M., "Finding pareto optimal front for the multi-mode time, cost quality trade-off in project scheduling", World Academy of Science, Engineering and Technology,  Vol. 40, (2008), 346-350.

18.   El Razek, R.H.A., Diab, A.M., Hafez, S.M. and Aziz, R.F., "Time-cost-quality trade-off software by using simplified genetic algorithm for typical-repetitive construction projects", World Academy of Science, Engineering and Technology,  Vol. 37, (2010), 312-320.

19.   Rahimi, M. and Iranmanesh, H., "Multi objective particle swarm optimization for a discrete time, cost and quality trade-off problem", World Applied Sciences Journal,  Vol. 4, No. 2, (2008), 270-276.

20.   Shahsavari-Pour, N., Modarres, M., Tavakoli-Moghadam, R. and Najafi, E., "Optimizing a multi-objectives time-cost-quality trade-off problem by a new hybrid genetic algorithm", World Applied Science Journal,  Vol. 10, No. 3, (2010), 355-363.

21.   Mokhtari, H., Kazemzadeh, R.B. and Salmasnia, A., "Time-cost tradeoff analysis in project management: An ant system approach", IEEE Transactions on engineering management,  Vol. 58, No. 1, (2011), 36-43.

22.   Kim, J., Kang, C. and Hwang, I., "A practical approach to project scheduling: Considering the potential quality loss cost in the time–cost tradeoff problem", International Journal of Project Management,  Vol. 30, No. 2, (2012), 264-272.

23.   Baradaran, S., Ghomi, S.F., Ranjbar, M. and Hashemin, S., "Multi-mode renewable resource-constrained allocation in pert networks", Applied Soft Computing,  Vol. 12, No. 1, (2012), 82-90.

24.   Li, H. and Zhang, H., "Ant colony optimization-based multi-mode scheduling under renewable and nonrenewable resource constraints", Automation in Construction,  Vol. 35, (2013), 431-438.

25.   Afshar-Nadjafi, B. and Majlesi, M., "Resource constrained project scheduling problem with setup times after preemptive processes", Computers & Chemical Engineering,  Vol. 69, (2014), 16-25.

26.   Bagherinejad, J. and Majd, Z.R., "Solving the mrcpsp/max with the objective of minimizing tardiness/earliness cost of activities with double genetic algorithms", The International Journal of Advanced Manufacturing Technology,  Vol. 70, No. 1-4, (2014), 573-582.

27.   Zheng, H., "Multi-mode discrete time-cost-environment trade-off problem of construction systems for large-scale hydroelectric projects", in Proceedings of the ninth international conference on management science and engineering management, Springer., (2015), 337-346.

28.   Chakrabortty, R.K., Sarker, R.A. and Essam, D.L., "Multi-mode resource constrained project scheduling under resource disruptions", Computers & Chemical Engineering,  Vol. 88, (2016), 13-29.

29.   Zou, P.X., Zhang, G. and Wang, J., "Understanding the key risks in construction projects in china", International Journal of Project Management,  Vol. 25, No. 6, (2007), 601-614.

30.   Subramanyan, H., Sawant, P.H. and Bhatt, V., "Construction project risk assessment: Development of model based on investigation of opinion of construction project experts from india", Journal of Construction Engineering and Management,  Vol. 138, No. 3, (2012), 409-421.

31.   Fang, C. and Marle, F., "A simulation-based risk network model for decision support in project risk management", Decision Support Systems,  Vol. 52, No. 3, (2012), 635-644.

32.   Fulkerson, D.R., "A network flow computation for project cost curves", Management Science,  Vol. 7, No. 2, (1961), 167-178.

33.   Siemens, N., "A simple cpm time-cost tradeoff algorithm", Management Science,  Vol. 17, No. 6, (1971), B-354-B-363.

34.   Adel, S.M. and Elmaghraby, S.E., "Optimal linear approximation in project compression", IIE Transactions,  Vol. 16, No. 4, (1984), 339-347.

35.   Falk, J.E. and Horowitz, J.L., "Critical path problems with concave cost-time curves", Management Science,  Vol. 19, No. 4-part-1, (1972), 446-455.

36.   Kapur, K.C., "An algorithm for project cost-duration analysis problem with quadratic and convex cost functions", AIIE Transactions,  Vol. 5, No. 4, (1973), 314-322.

37.   De, P., Dunne, E.J., Ghosh, J.B. and Wells, C.E., "The discrete time-cost tradeoff problem revisited", European Journal of Operational Research,  Vol. 81, No. 2, (1995), 225-238.

38.   Pour, N.S., Modarres, M., Aryanejad, M.B. and Moghadam, R.T., "Calculating the project network critical path in uncertainty conditions",  International Journal of Engineering and Technology, Vol. 2, No. 2, (2010), 136-140.

39.   Tavana, M., Abtahi, A.-R. and Khalili-Damghani, K., "A new multi-objective multi-mode model for solving preemptive time–cost–quality trade-off project scheduling problems", Expert Systems with Applications,  Vol. 41, No. 4, (2014), 1830-1846.

40.   S.H., Z., E., R., Nazari, A. and Honarichbar, F., "Evaluating and selecting risk response strategies using multiple objective optimization model and fuzzy prioritizing approach in abadan power plant", Technology Research and Development Journal,  Vol. 5, No. 4, (2012), 393-400.

41.   Chapman, C. and Ward, S., "Project risk management: Processes, techniques, and insights",  2nd Ed., Chichester, John Wiley & Sons (2003).

42.   Sato, T. and Hirao, M., "Optimum budget allocation method for projects with critical risks", International Journal of Project Management,  Vol. 31, No. 1, (2013), 126-135.

43.   van der Plas, C., Tervonen, T. and Dekker, I.R., “Evolutionary multi-objective optimization and preference modeling in green logistics”, Economie & Informatica, Retrieved from http://hdl.handle.net/2105/11492, (2012).

44.   Neri, F., Cotta, C. and Moscato, P., "Handbook of memetic algorithms, Springer,  Vol. 379,  (2012).