Robust forensic-based investigation algorithm for resource leveling in multiple projects

Document Type : Article

Authors

1 - Faculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City, Vietnam. - Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam.

2 - Faculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City, Vietnam. - Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam. - Faculty of Civil Engineering, Can Tho University of Technology (CTUT), Can Tho City, Vietnam.

3 Faculty of Building and Industrial Construction, Hanoi University of Civil Engineering (HUCE), Ha Noi, Vietnam.

4 - Faculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City, Vietnam. - Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam. - Binh Duong University, Thu Dau Mot City, Vietnam

Abstract

The project managers often face challenging due to a scarcity of resources in construction management. Levelling the used resources in multiple projects is a frequently encountered problem in construction areas and manufacturing sectors. This study proposes a robust forensic-based investigation (FBI) algorithm for resource leveling in multiple projects with considerations of different objective functions of resource graphs. The fuzzy c-means clustering approach is fused into the main operation of the FBI to enhance the rate of convergence by utilizing population information. The scheduling examines different objective functions for optimizing resource profile selection. Two application case studies are used to demonstrate the performance of the improved optimization algorithm in dealing with the resource-leveling problem in multiple projects. Experimental findings and statistical comparisons demonstrated that the developed FFBI could acquire high quality solutions and surpass those of compared optimization algorithms.

Keywords

References

References:
1. Selvam, G. and Tadepalli, T.C.M. "Genetic algorithm based optimization for resource leveling problem with precedence constrained scheduling", International Journal of Construction Management, pp. 1-10 (2019). DOI: 10.1080/15623599.2019.1641891.
2. Damci, A., Polat, G., Akin, F.D., et al. "Use of  float consumption rate in resource leveling of construction projects", Frontiers of Engineering Management, 9, pp. 135-147 (2022). DOI: 10.1007/s42524-020-0118-0.
3. Ammar, M.A. "Resource optimisation in line of balance scheduling", Construction Management and Economics, 38(8), pp. 715-725 (2020). DOI: 10.1080/01446193.2019.1606924.
4. Kong, F. and Dou, D. "RCPSP with combined precedence relations and resource calendars", Journal of Construction Engineering and Management, 146(12), 04020133 (2020). DOI: 10.1061/(asce)co.1943-7862.0001929.
5. Wang, Z., Hu, Z., and Tang, Y. "Float-based resource leveling optimization of linear projects", IEEE Access, 8, pp. 176997-177020 (2020). DOI: 10.1109/access. 2020.3027058.
6. Kazemi, S. and Davari-Ardakani, H. "Integrated resource leveling and material procurement with variable execution intensities", Computers & Industrial Engineering, 148, 106673 (2020). DOI: 10.1016/j.cie.2020.106673.
7. Li, H., Xiong, L., Liu, Y., et al. "An effective genetic algorithm for the resource levelling problem with generalised precedence relations", International Journal of Production Research, 56(5), pp. 2054-2075 (2018). DOI: 10.1080/00207543.2017.1355120.
8. Almatroushi, H., Hariga, M., As'ad, R., et al. "The multi resource leveling and materials procurement problem: An integrated approach", Engineering, Construction and Architectural Management, 27(9), pp. 2135-2161 (2020). DOI: 10.1108/ecam-10-2019-0563.
9. Banihashemi, S.A. and Khalilzadeh, M. "A robust bi-objective optimization model for resource levelling project scheduling problem with discounted cash flows", KSCE Journal of Civil Engineering, 26(6), pp. 2539-2554 (2022). DOI: 10.1007/s12205-022-0679-z.
10. Khalilzadeh, M. "Resource levelling in projects considering different activity execution modes and splitting", Journal of Engineering, Design and Technology, 20(5), pp. 1073-1100 (2022). DOI: 10.1108/jedt-11-2020-0463.
11. Damci, A. and Polat, G. "Impacts of different objective functions on resource leveling in construction projects: A case study", Journal of Civil Engineering and Management, 20(4), pp. 1-11 (2014). DOI:10.3846/13923730.2013.801909.
12.Ponz-Tienda, J.L., Yepes, V., Pellicer, E., et al. "The resource leveling problem with multiple resources using an adaptive genetic algorithm", Automation in Construction, 29, pp. 161-172 (2013). DOI: 10.1016/j.autcon.2012.10.003.
13. Wang, H.-X., Wang, Z.-H., and Zhu, M. "Differential evolution algorithm for multi-project resource leveling problem", Journal of Interdisciplinary Mathematics, 20(6-7), pp. 1383-1386 (2017). DOI:10.1080/09720502.2017.1382141.
14. Cheng, M., Prayogo, D., and Tran, D. "Optimizing multiple-resources leveling in multiple projects using discrete symbiotic organisms search", Journal of Computing in Civil Engineering, 30(3), 04015036 (2016).DOI: 10.1109/icnc.2009.142.
15. Sayyadi, A., Esmaeeli, H., and Hosseinian, A.H. "A community detection approach for the resource leveling problem in a multi-project scheduling environment", Computers & Industrial Engineering, 169, 108202 (2022). DOI: 10.1061/(asce)cp.1943- 5487.0000512.
16. Yan, G., Nan, L., and Tingting, Y. "Multiple resources leveling in multiple projects scheduling problem using particle swarm optimization", Fifth International Conference on Natural Computation, 3, Tianjian, China: IEEE (2009). DOI: 10.1016/j.cie.2022.108202.
17. Vikhar, P.A. "Evolutionary algorithms: A critical review and its future prospects", International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), (2016). DOI: 10.1109/icgtspicc.2016.7955308.
18. Chakraborty, K., Deb, G., and Sharma, S. "Symbiotic organisms search based multi-objective optimal placement of distributed generators considering uncertainty of source and load", Scientia Iranica, 30(2), pp. 518- 535 (2023). DOI: 10.24200/sci.2021.56149.4575.
19. Erden, C., Demir, H.I., and Canpolat, O. "A modified integer and categorical PSO algorithm for solving integrated process planning, dynamic scheduling and due date assignment problem", Scientia Iranica, 30(2), pp. 738-756 (2023). DOI: 10.24200/sci.2021.55250.4130.
20. Can, E., Ustun, O., and Saglam, S. "Metaheuristic approach proposal for the solution of the bi-objective course scheduling problem", Scientia Iranica, 30(4), pp. 1435-1449 (2023). DOI: 10.24200/sci.2021.55005.4044.
21. Chou, J.-S. and Nguyen, N.-M. "FBI inspired metaoptimization", Applied Soft Computing, 93, 106339 (2020). DOI: 10.1016/j.asoc.2020.106339.
22. Fathy, A., Rezk, H., and Alanazi, T.M. "Recent approach of forensic-based investigation algorithm for optimizing fractional order PID-based MPPT with proton exchange membrane fuel cell", IEEE Access, 9, pp. 18974-18992 (2021). DOI: 10.1109/access. 2021.3054552.
23. Kuyu, Y.C . and Vatansever, F. "Modified forensicbased investigation algorithm for global optimization", Engineering with Computers, 38, pp. 3197-3218 (2022). DOI: 10.1007/s00366-021-01322-w.
24. Shaheen, A.M., Ginidi, A.R., El-Sehiemy, R.A., et al. "A forensic-based investigation algorithm for parameter extraction of solar cell models", IEEE Access, 9, pp. 1-20 (2021). DOI: 10.1109/access.2020.3046536.
25. Kaveh, A., Hamedani, K.B., and Kamalinejad, M. "An enhanced forensic-based investigation algorithm  and its application to optimal design of frequencyconstrained dome structures", Computers & Structures, 256, 106643 (2021). DOI: 10.1016/j.compstruc.2021.106643.
26. Li, H. and Dong, X. "Multi-mode resource leveling in projects with mode-dependent generalized precedence relations", Expert Systems with Applications, 97, pp. 193-204 (2018). DOI: 10.1016/j.eswa.2017.12.030.
27. Pellerin, R. and Perrier, N. "A review of methods, techniques and tools for project planning and control", International Journal of Production Research, 57(7), pp. 2160-2178 (2019). DOI: 10.1080/00207543.2018.1524168.
28. Derbe, G., Li, Y., Wu, D., et al. "Scientometric review of construction project schedule studies: trends, gaps and potential research areas", Journal of Civil Engineering and Management, 26(4), pp. 343-363 (2020). DOI: 10.1080/00207543.2018.1524168.
29. Zhou, J., Love, P.E.D., Wang, X., et al. "A review of methods  and algorithms for optimizing construction scheduling", Journal of the Operational Research Society, 64(8), pp. 1091-1105 (2013). DOI: 10.1057/jors.2012.174.
30. Chan, W.-T., Chua, D.K.H., and Kannan, G. "Construction resource scheduling with genetic algorithms",  Journal of Construction Engineering and Management, 122(2), pp. 125-132 (1996). DOI: 10.1061/(asce)0733-9364(1996)122:2(125).
31. Bandelloni, M., Tucci, M., and Rinaldi, R. "Optimal resource leveling using non-serial dyanamic programming", European Journal of Operational Research, 78(2), pp. 162-177 (1994). DOI: 10.1016/0377- 2217(94)90380-8.
32. Hariga, M. and El-Sayegh, S.M. "Cost optimization model for the multiresource leveling problem with allowed activity splitting", Journal of Construction Engineering and Management, 137(1), pp. 56-64 (2011). DOI: 10.1061/(asce)co.1943-7862.0000251.
33. Younis, M.A. and Saad, B. "Optimal resource leveling of multi-resource projects", Computers and Industrial Engineering, 31(1-2), pp. 1-4 (1996). DOI: 10.1016/0360-8352(96)00116-7.
34. Alinaghian, M., Hejazi, S.R., Bajoul, N., et al. "A novel robust model for health care facilities locationallocation considering pre disaster and post disaster characteristics", Scientia Iranica, 30(2), pp. 619-641 (2023). DOI: 10.24200/sci.2021.5743.1459.
35. Amiri, F. "Optimization of facility location-allocation model for base tranceiver station antenna establishment based on genetic algorithm considering network effectiveness criteria (Case study North of Kermanshah)", Scientia Iranica, 30(5), pp. 1841-1854 (2023). DOI: 10.24200/sci.2021.55207.4116.
36. Harris, R.B. "Packing method for resource leveling (Pack)", Journal of Construction Engineering and Management, 116(2), pp. 331-350 (1990). DOI: 10.1061/(asce)0733-9364(1990)116:2(331).
37. Neumann, K. and Zimmermann, J. "Procedures for resource leveling and net present value problems in project scheduling with general temporal and resource constraints", European Journal of Operational Research, 127(2), pp. 425-443 (2000). DOI: 10.1061/(asce)0733-9364(1999)125:1(23).
38. Son, J. and Skibniewski Miroslaw, J. "Multiheuristic approach for resource leveling problem in construction engineering: Hybrid approach", Journal of Construction Engineering and Management, 125(1), pp. 23-31 (1999). DOI: 10.1016/s0377-2217(99)00498-1.
39. Yan, L., Sheng-Li, Z., Xi-Kai, D., et al. "Optimization of resource allocation in construction using genetic algorithms", International Conference on Machine Learning and Cybernetics, 6, Guangzhou, China: IEEE (2005). DOI: 0.1109/icmlc.2005.1527534.
40. Xu, X., Hao, J., and Zheng, Y. "Multi-objective artificial bee colony algorithm for multi-stage resource leveling problem in sharing logistics network", Computers & Industrial Engineering, 142, 106338 (2020). DOI: 10.1016/j.cie.2020.106338.
41. Hegazy, T. "Optimization of resource allocation and leveling using genetic algorithms", Journal of Construction Engineering and Management, 125(3), pp. 167-175 (1999). DOI: 10.1061/(asce)0733-9364(1999)125:3(167).
42. Leu, S.-S., Yang, C.-H., and Huang, J.-C. "Resource leveling in construction by genetic algorithm-based optimization and its decision support system application", Automation in Construction, 10(1), pp. 27-41 (2000). DOI: 10.1016/s0926-5805(99)00011-4.
43. Li, H. and Demeulemeester, E. "A genetic algorithm for the robust resource leveling problem", Journal of Scheduling, 19(1), pp. 43-60 (2016). DOI: 10.1007/s10951-015-0457-6.
44. Senouci, A.B. and Eldin, N.N. "Use of genetic algorithms in resource scheduling of construction projects", Journal of Construction Engineering and Management, 130(6), pp. 869-877 (2004). DOI: 10.1061/(asce)0733-9364(2004)130:6(869).
45. Geng, J.-Q., Weng, L.-P., and Liu, S.-H. "An improved ant colony optimization algorithm for nonlinear resource-leveling problems", Computers & Mathematics with Applications, 61(8), pp. 2300-2305 (2011). DOI: 10.1109/icnc.2009.142.
46. Tran, D.-H., Cheng, M.-Y., and Pham, A.-D. "Using fuzzy clustering chaotic-based differential evolution to solve multiple resources leveling in the multiple projects scheduling problem", Alexandria Engineering Journal, 55(2), pp. 1541-1552 (2016). DOI: 10.1016/j.camwa.2010.09.058.
47. Cheng, M.-Y., Tran, D.-H., and Hoang, N.-D. "Fuzzy clustering chaotic-based differential evolution for resource leveling in construction projects", Journal of Civil Engineering and Management, 23(1), pp. 113- 124 (2017). DOI: 10.1016/j.aej.2016.03.038.
48. Khanzadi, M., Kaveh, A., Alipour, M., et al. "Application of CBO and CSS for resource allocation and resource leveling problem", Iranian Journal of Science and Technology, Transactions of Civil Engineering, 40(1), pp. 1-10 (2016). DOI: 10.3846/13923730.2014.982699.
49. Prayogo, D., Cheng, M.-Y., Wong, F.T., et al. "Optimization model for construction project resource leveling using a novel modified symbiotic organisms search", Asian Journal of Civil Engineering, 19(5), pp. 625-638 (2018). DOI: 10.1007/s40996-016-0004-5.
50. Cheng, M.-Y., Prayogo, D., and Tran, D.-H. "Optimizing multiple-resources leveling in multiple projects using discrete symbiotic organisms search", Journal of Computing in Civil Engineering, 30(3), 04015036 (2016). DOI: 10.1007/s42107-018-0048-x.
51. Tzanetos, A., Ntardas, D., and Dounias, G. "Resource leveling optimization in construction projects of high voltage substations using nature inspired intelligent evolutionary algorithms", International Journal of Electrical and Computer Engineering, 14(1), pp. 6-13 (2021). DOI: 10.1061/(asce)cp.1943-5487.0000512.
52. Masmoudi, M. and Hait, A. "Project scheduling under uncertainty using fuzzy modelling and solving techniques", Engineering Applications of Artificial Intelligence, 26(1), pp. 135-149 (2013). DOI: 10.5281/zenodo. 3607880.
53. Kyriklidis, C., Vassiliadis, V., Kirytopoulos, K., et al. "Hybrid nature-inspired intelligence for the resource leveling problem", Operational Research, 14(3), pp. 387-407 (2014). DOI: 10.1016/j.engappai.2012.07.012.
54. Damci, A., Arditi, D., and Polat, G. "Impacts of different objective functions on resource leveling in line-ofbalance scheduling", KSCE Journal of Civil Engineering, 20(1), pp. 58-67 (2016). DOI: 10.1007/s12351- 014-0145-x.
55. Guo, Y., Li, N., and Ye, T. "Multiple resources leveling in multiple projects scheduling problem using particle swarm optimization", Natural Computation, 2009. ICNC '09. Fifth International Conference on, 3, (2009). DOI: 10.1007/s12205-015-0578-7.
56. Policing, C.O. "Investigation process", Available: https://www.app.college.police.uk/appcontent/ investigations/investigation-process/ (2013). 
57. Salet, R. "Framing in criminal investigation: How police officers (re) construct a crime", The Police Journal, 90(2), pp. 128-142 (2017). DOI: 10.1177/0032258x16672470.
58. Cai, Z., Gong, W., Ling, C.X., et al. "A clusteringbased differential evolution for global optimization", Applied Soft Computing, 11(1), pp. 1363-1379 (2011).  DOI: 10.1016/j.asoc.2010.04.008.
59. Deb, K. "A population-based algorithm-generator for real-parameter optimization", Soft Computing, 9(4), pp. 236-253 (2005). DOI: 10.1007/s00500-004-0377-4.
60. Haupt, R.L. and Haupt, S.E., Practical Genetic Algorithms, John Wiley & Sons, Inc. NJ (2004). DOI: DOI:10.1002/0471671746.
61. Clerc, M., Particle Swarm Optimization, ISTE Ltd, London (2006). 62. Storn, R. and Price, K. "Differential evolution - A simple and efficient heuristic for global optimization over continuous spaces", (in English), Journal of Global Optimization, 11(4), pp. 341-359 (1997). DOI: 10.1023/A:1008202821328.
63. Cheng, M.-Y. and Prayogo, D. "Symbiotic organisms search: A new metaheuristic optimization algorithm", Computers & Structures, 139, pp. 98-112 (2014). DOI: 10.1016/j.compstruc.2014.03.007.
64. Mirjalili, S. and Lewis, A. "The whale optimization algorithm", Advances in Engineering Software, 95, pp. 51-67 (2016). DOI: 10.1016/j.advengsoft.2016.01.008.
Scientia Iranica
Volume 31, Issue 7
Transactions on Civil Engineering (A)
May and June 2024
Pages 603-618

Files

Share

How to cite

Statistics