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Reducing renewable resource demand fluctuation using soft precedence relations in project scheduling

    Piotr Jaskowski   Affiliation
    ; Slawomir Biruk   Affiliation

Abstract

Renewable resource levelling is the core of the scheduling process. A perfect schedule ensures that resource supply corresponds to the demand at every unit of project time. A classic approach to resource levelling in schedules with predefined project completion dates consists in manipulating processes start dates. Resource deployment can be also improved by considering alternative construction processes execution modes with various crew formations, and by allowing activities to be split. There are other possibilities: in many practical cases, the activities’ precedence logic predefined in the network model can be changed with no harm to the project outcome. Within the structure of the project network model, some precedence relations between activities would definitely be of fixed (hard) character, whereas some might allow the activities to be executed at the same time or arranged in a variety of logical sequences. The authors use soft precedence relations that let the processes run in reversed order or that can be cancelled, in search for improved resource usage profiles. The benefits of scheduling with soft precedence relations are demonstrated by an example.

Keyword : construction project management, project scheduling, renewable resource levelling, resource utilization, soft logic, schedule optimization

How to Cite
Jaskowski, P., & Biruk, S. (2018). Reducing renewable resource demand fluctuation using soft precedence relations in project scheduling. Journal of Civil Engineering and Management, 24(4), 355-363. https://doi.org/10.3846/jcem.2018.3043
Published in Issue
Jul 11, 2018
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Anagnostopoulos, K. P.; Koulinas, G. K. 2010. A simulated annealing hyperheuristic for construction resource levelling, Construction Management and Economics 28(2): 163–175. https://doi.org/10.1080/01446190903369907

Ballestín, F.; Schwindt, C.; Zimmermann, J. 2007. Resource leveling in make–to–order production: modeling and heuristic solution method, International Journal of Operations Research 4(1): 50–62.

Bandelloni, M.; Tucci, M.; Rinaldi, R. 1994. Optimal resource leveling using non–serial dynamic programming, European Journal of Operational Research 78(2): 162–177. https://doi.org/10.1016/0377-2217(94)90380-8

Benjaoran, V.; Tabyang, W.; Sooksil, N. 2015. Precedence relationship options for the resource levelling problem using a genetic algorithm, Construction Management and Economics 33(9): 711–723. https://doi.org/10.1080/01446193.2015.1100317

Chan, W.-T.; Chua, D. K. H.; Kannan, G. 1996. Construction resource scheduling with genetic algorithms, Journal of Construction Engineering and Management 122: 125–132. https://doi.org/10.1061/(ASCE)0733-9364(1996)122:2(125)

Christodoulou, S. E.; Ellinas, G.; Michaelidou-Kamenou, A. 2010. Minimum moment method for resource leveling using entropy maximization, Journal of Construction Engineering and Management 136(5): 518–527. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000149

Easa, S. M. 1989. Resource leveling in construction by optimization, Journal of Construction Engineering and Management 115(2): 302–316. https://doi.org/10.1061/(ASCE)0733-9364(1989)115:2(302)

Gather, T.; Zimmermann, J.; Bartels, J. H. 2011. Exact methods for the resource levelling problem, Journal of Scheduling 14(6): 557–569. https://doi.org/10.1007/s10951-010-0207-8

Geng, J. Q.; Weng, L. P.; Liu, S. H. 2011. An improved ant colony optimization algorithm for nonlinear resource-leveling problems, Computers & Mathematics with Applications 61(8): 2300–2305. https://doi.org/10.1016/j.camwa.2010.09.058

Hariga, M.; El-Sayegh, S. M. 2011. Cost optimization model for the multiresource leveling problem with allowed activity splitting, Journal of Construction Engineering and Management 137(1): 56–64. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000251

Harris, B. R. B. 1990. Packing method for resource leveling (Pack), Journal of Construction Engineering and Management 116(2): 331–350. https://doi.org/10.1061/(ASCE)0733-9364(1990)116:2(331)

He, L.; Zhang, L. 2013. Dynamic priority rule-based forward-backward heuristic algorithm for resource levelling problem in construction project, Journal of the Operational Research Society 64(8): 1106–1117. https://doi.org/10.1057/jors.2013.33

Iyer, P.; Liu, Y.; Sadeghpour, F.; Brennan, R. W. 2015. A fuzzy-logic based resource levelling optimisation tool, IFAC–PapersOnLine 28: 1942–1947. https://doi.org/10.1016/j.ifacol.2015.06.371

Jaskowski, P. 2008. Designing the structure of a construction project operating system using evolutionary algorithm, Archives of Civil Engineering 54(2): 371–394.

Jaskowski, P.; Sobotka, A. 2012. Using soft precedence relations for reduction of the construction project duration, Technological and Economic Development of Economy 18(2): 262–279. https://doi.org/10.3846/20294913.2012.666217

Kaiafa, S.; Chassiakos, A. P. 2015. A genetic algorithm for optimal resource–driven project scheduling, Procedia Engineering 123: 260–267. https://doi.org/10.1016/j.proeng.2015.10.087

Karaa, F. A.; Nasr, A. Y. 1986. Resource management in construction, Journal of Construction Engineering and Management 112(3): 346–357. https://doi.org/10.1061/(ASCE)0733-9364(1986)112:3(346)

Koulinas, G. K.; Anagnostopoulos, K. P. 2013. A new tabu search-based hyper-heuristic algorithm for solving construction leveling problems with limited resource availabilities, Automation in Construction 31: 169–175. https://doi.org/10.1016/j.autcon.2012.11.002

Leu, B. S.; Yang, C. 1999. GA-based multicriteria optimal for construction scheduling, Journal of Construction Engineering and Management 125: 420–427. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:6(420)

Leu, S. S.; Yang, C. H.; Huang, J. C. 2000. Resource leveling in construction by genetic algorithm-based optimization and its decision support system application, Automation in Construction 10(1): 27–41. https://doi.org/10.1080/01446193.2015.1100317

Mattila, K. G.; Abraham, D. M. 1998. Resource leveling of linear schedules using integer linear programming, Journal of Construction Engineering and Management 124(3): 232–244. https://doi.org/10.1061/(ASCE)0733-9364(1998)124:3(232)

Ponz-Tienda, J. L.; Yepes, V.; Pellicer, E.; Moreno-Flores, J. 2013. The resource leveling problem with multiple resources using an adaptive genetic algorithm, Automation in Construction 29: 161–172. https://doi.org/10.1016/j.autcon.2012.10.003

Radziszewska-Zielina, E. 2010. Analysis of the impact of the level of partnering relations on the selected indexes of success of Polish construction enterprises, Inzinerine Ekonomika - Engineering Economics 21(3): 324–335.

Rieck, J.; Zimmermann, J.; Gather, T. 2012. Mixed-integer linear programming for resource leveling problems, European Journal of Operational Research 221(1): 27–37. https://doi.org/10.1016/j.ejor.2012.03.003

Savin, D.; Alkass, S.; Fazio, P. 1996. Construction resource leveling using neural networks, Canadian Journal of Civil Engineering 23(4): 917–925. https://doi.org/10.1139/l96-898

Senouci, A. B.; Eldin, N. N.; Asce, M. 2004. Use of genetic algorithms in resource scheduling of construction projects, Journal of Construction Engineering and Management 130(6): 869–877. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:6(869)

Shao, M.; Liu, X. 2015. Control indicators for resource leveling in project network planning, in Proceedings of the 2015 International Conference on Applied Science and Engineering Innovation, 1097–2002. https://doi.org/10.2991/asei-15.2015.217

Son, J.; Mattila, K. G. 2004. Binary resource leveling model: activity splitting allowed, Journal of Construction Engineering and Management 130(6): 887–894. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:6(887)

Son, J.; Skibniewski, M. J. 1999. Multiheuristic approach for resource leveling problem in construction engineering: hybrid approach, Journal of Construction Engineering and Management 125: 23–31. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:1(23)

Tamimi, S.; Diekmann, J. 1988. Soft logic in network analysis, Journal of Computing in Civil Engineering 2(3): 289–300. https://doi.org/10.1061/(ASCE)0887-3801(1988)2:3(289)

Wagner, H. M.; Giglio, R. J.; Glaser, R. G. 1964. Preventive maintenance scheduling by mathematical programming, Management Science 10(2): 316–334. https://doi.org/10.1287/mnsc.10.2.316

Zhang, H.; Li, H.; Tam, C. M. 2006. Particle swarm optimization for resource-constrained project scheduling, International Journal of Project Management 24(1): 83–92. https://doi.org/10.1016/j.ijproman.2005.06.006