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Invisible consumptions and enlargements of activity floats under generalized precedence relations

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Abstract

Generalized precedence relations (GPRs) between activities widely exist in modern construction projects. Time floats of activities (activity floats) are indispensable to arrange the activities to cope with unstable external conditions. This paper discovers that the GPRs result in new singularities of activity floats—time floats of an activity can be consumed and enlarged imperceptibly even if the activity has not started and all activities don’t consume their time floats. The singularities are called invisible consumptions and enlargements of activity floats. This paper analyzes the singularities and presents algorithms to identify and quantize them. The new singular characteristics of activity floats may weaken current optimization approaches for project scheduling. Inspired by the characteristics, this paper develops an emergency resource leveling with GPRs that focuses on emergency actions for the dynamic and uncertain environment. An illustration demonstrates that the correct solution relies on the invisible consumptions and enlargements of activity floats.

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References

  • Alfieri A, Tolio T, Urgo M (2011) A project scheduling approach to production planning with feeding precedence relations. Int J Prod Res 49:995–1020

    Article  Google Scholar 

  • Amin F, Fahmi A, Abdullah S, Ali A, Ahmed R, Ghani F (2017) Triangular cubic linguistic hesitant fuzzy aggregation operators and their application in group decision making. J Intell Fuzzy Syst 34:2401–2416

    Article  Google Scholar 

  • Bartusch M, Möhring RH, Radermacher FJ (1988) Scheduling project networks with resource constraints and time windows. Ann Oper Res 16:201–240

    Article  MathSciNet  Google Scholar 

  • Bianco L, Caramia M (2011) A new lower bound for the resource-constrained project scheduling problem with generalized precedence relations. Comput Oper Res 38:14–20

    Article  MathSciNet  Google Scholar 

  • Bianco L, Caramia M (2012) An exact algorithm to minimize the makespan in project scheduling with scarce resources and generalized precedence relations. Eur J Oper Res 219:73–85

    Article  MathSciNet  Google Scholar 

  • Bianco L, Caramia M, Giordani S (2016) Resource levelling in project scheduling with generalized precedence relationships and variable execution intensities. OR Spectrum 38:405–425

    Article  MathSciNet  Google Scholar 

  • Brinkmann K, Neumann K (1996) Heuristic procedures for resource-constrained project scheduling with minimal and maximal time lags: the resource-levelling and minimum projectduration problems. J Decis Syst 5:129–155

    Article  Google Scholar 

  • Damci A, Arditi D, Polat G (2013) Resource leveling in line-of-balance scheduling. Comput Aided Civ Infrastruct Eng 28:679–692

    Article  Google Scholar 

  • Damci A, Arditi D, Polat G (2016) Impacts of different objective functions on resource leveling in line-of-balance scheduling. KSCE J Civ Eng 20:58–67

    Article  Google Scholar 

  • Dorndorf U, Pesch E, Phan-Huy T (2000) A time-oriented branch-and-bound algorithm for resource-constrained project scheduling with generalised precedence constraints. Manag Sci 46:1365–1384

    Article  Google Scholar 

  • Easa SM (1989) Resource leveling in construction by optimization. J Constr Eng Manag 115:302–316

    Article  Google Scholar 

  • Elmaghraby SE, Kamburowski J (1992) The analysis of activity networks under generalized precedence relations (GPRs). Manag Sci 38:1245–1263

    Article  Google Scholar 

  • Fahmi A, Amin F, Abdullah S, Ali A (2018a) Cubic fuzzy Einstein aggregation operators and its application to decision making. Int J Syst Sci 49:2385–2397

    Article  MathSciNet  Google Scholar 

  • Fahmi A, Abdullah S, Amin F, Ali A, Khan WA (2018b) Some geometric operators with triangular cubic linguistic hesitant fuzzy number and their application in group decision-making. J Intell Fuzzy Syst 35:2485–2499

    Article  Google Scholar 

  • Fahmi A, Abdullah S, Amin F, Khan MSA (2018c) Trapezoidal cubic fuzzy number einstein hybrid weighted averaging operators and its application to decision making. Soft Comput 1–31. https://doi.org/10.1007/s00500-018-3242-6

  • Fahmi A, Abdullah S, Amin F, Siddque N, Ali A (2017) Aggregation operators on triangular cubic fuzzy numbers and its application to multi-criteria decision making problems. J Intell Fuzzy Syst 33:3323–3337

    Article  Google Scholar 

  • George SJ (1988) Time-the next source of competitive advantage. Harv Bus Rev 66:41–51

    Google Scholar 

  • José LPT, Eugenio P, Javier BM, Carlos AR (2015) The fuzzy project scheduling problem with minimal generalized precedence relations. Comput Aided Civ Infrastruct Eng 30:872–891

    Article  Google Scholar 

  • Li H, Dong X (2018) Multi-mode resource leveling in projects with mode-dependent generalized precedence relations. Expert Syst Appl 97:193–204

    Article  Google Scholar 

  • Kaveh KD, Madjid T, Abtahi AR, Francisco JSA (2015) Solving multi-mode time-cost-quality trade-off problems under generalized precedence relations. Optim Methods Softw 30:965–1001

    Article  MathSciNet  Google Scholar 

  • Mattila KG, Abraham DM (1998) Linear scheduling: past resource efforts and future directions. Eng Constr Archit Manag 5:294–303

    Article  Google Scholar 

  • Mubarak SA (2010) Construction project scheduling and control, 2nd edn. Wiley, Hoboken

    Book  Google Scholar 

  • Neetesh K, Deo V (2016) A model for resource-constrained project scheduling using adaptive PSO. Soft Comput 20:1565–1580

    Article  Google Scholar 

  • Neumann K, Zimmermann J (2000) Procedures for resource levelling and net present value problems in project scheduling with general temporal and resource constraints. Eur J Oper Res 127:425–443

    Article  Google Scholar 

  • Pawel M, Marek S, Lukasz O, Krzysztof O (2015) Hybrid ant colony optimization in solving multi-skill resource-constrained project scheduling problem. Soft Comput 19:3599–3619

    Article  Google Scholar 

  • Peng W, Huang M (2014) A critical chain project scheduling method based on a differential evolution algorithm. Int J Prod Res 52:3940–3949

    Article  Google Scholar 

  • Pérez Á, Quintanilla S, Lino P, Valls V (2014) A multi-objective approach for a project scheduling problem with due dates and temporal constraints infeasibilities. Int J Prod Res 52:3950–3965

    Article  Google Scholar 

  • Pérez E, Posada M, Lorenzana A (2016) Taking advantage of solving the resource constrained multi-project scheduling problems using multi-modal genetic algorithms. Soft Comput 20:1879–1896

    Article  Google Scholar 

  • Qi J, Su Z (2014) Analysis of an anomaly: the increase in time float following consumption. Sci World J 2014:415870-1–415870-12

    Google Scholar 

  • Quintanilla S, Pérez Á, Lino P, Valls V (2012) Time and work generalised precedence relationships in project scheduling with pre-emption: an application to the management of service centres. Eur J Oper Res 219:59–72

    Article  MathSciNet  Google Scholar 

  • Ranjbar M (2013) A path-relinking metaheuristic for the resource levelling problem. J Oper Res Soc 64:1071–1078

    Article  Google Scholar 

  • Rieck J, Zimmermann J, Gather T (2012) Mixed-integer linear programming for resource leveling problems. Eur J Oper Res 221:27–37

    Article  MathSciNet  Google Scholar 

  • Roy B (1962) Graphes et ordonnancements. Rev Fr Rech Oper 25:323–326

    Google Scholar 

  • Schnell A, Hartl R (2016) On the efficient modeling and solution of the multi-mode resource-constrained project scheduling problem with generalized precedence relations. OR Spectrum 38:283–303

    Article  MathSciNet  Google Scholar 

  • Shen S, Smith JC, Ahmed S (2010) Expectation and chance-constrained models and algorithms for insuring critical paths. Manag Sci 56:1794–1814

    Article  Google Scholar 

  • Su Z, Qi J, Kan Z (2015) Simplifying activity networks under generalized precedence relations to extended CPM networks. Int Trans Oper Res 23:1141–1161

    Article  MathSciNet  Google Scholar 

  • Tang Y, Liu R, Sun Q (2014) Two-stage scheduling model for resource leveling of linear projects. J Constr Eng Manag 140:04014022

    Article  Google Scholar 

  • Váncza J, Kis T, Kovcs A (2004) Aggregation: the key to integrating production planning and scheduling. Ann CIRP 53:374–376

    Article  Google Scholar 

  • Wiest JD (1981) Precedence diagramming method: some unusual characteristics and their implications for project managers. J Oper Manag 1:121–130

    Article  Google Scholar 

  • Zhang L, Pan C, Zou X (2013) Criticality comparison between repetitive scheduling method and network model. J Constr Eng Manag 139:06013004

    Article  Google Scholar 

  • Zhang L, Zou X, Kan Z (2014) Improved strategy for resource allocation in repetitive projects considering the learning effect. J Constr Eng Manag 140:04014053

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge the China Postdoctoral Science Foundation (Grant Number 2017M620713), and the Natural Science Foundation of Science and Technology Department of Jiangxi Province in China (Grant Number 20171BAA208001). The authors are grateful to the anonymous referee for a careful scrutiny of details and for comments that helped improve this paper.

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Appendices

Appendix A

A construction project aims to build a 6.3km part of a highway. The structure of a highway is very complicated. For the sake of simplicity I consider the three main structural layers of highway, A—a solid foundation (i.e., trenching, embankment, paving, etc.), B—a roadbed (i.e., cement pouring), and C—a surface layer (i.e., pavement decoration), as in Fig. 9.

Fig. 9
figure 9

Diagram of a highway construction

Normal operational modes of the three layers of construction involve linear pipeline construction. The solid foundation can be constructed in 27 meters per hour (m/h), the roadbed can be constructed in 30 m/h, and the surface layer can be constructed in 20 m/h. The minimum length between the solid foundation and the roadbed is 210 m, and the minimum length between the roadbed and surface layer is 150 m. The roadbed is a cement-stabilized structure that must be maintained for at least 7 h following cement stabilization.

The construction company decided to divide the highway into three 2.1km sections for construction (i.e., sections A, B and C were divided into \(A_k\), \(B_k\), and \(C_k\); \(k=1,2,3\)). Following this division, the durations of \(A_k\), \(B_k\), and \(C_k\) were found to be \(d_{A_k}=2100\div 27=78\hbox {h}\), \(d_{B_k}=2100\div 30=70\hbox {h}\), and \(d_{C_k}=2100\div 20=105\hbox {h}\), respectively. With respect to the partition, because \(B_k\) is a cement stable structure, after pouring cement in one part (\(B_k\)), the time lag before pouring cement in next part \(B_{k+1}\) should not be too long (not in excess of 12 hours in this example). Otherwise, the viscosity of the cement will fall and the surface of the road cannot be properly constructed. As such, the time lag method used here is the Finish-to-Start type of maximum time lag\(\hbox {FTS}_{B_{k}B_{k+1}}^{\max }(12)\), \(k=1,2\).

To facilitate the analysis, I transform the required distances between layers during construction into time lags. Meeting the required distance between two layers during construction is determined by the construction speed and chronological order of activities related to the construction of the two layers:

(1) For solid foundation (A) and roadbed (B), the construction speeds of \(A_k\) and \(B_k\) are 27 m/h and 30 m/h, respectively. The slower \(A_k\) lies ahead of the faster \(B_k\). This means that the distance between \(B_k\) and \(A_k\) will shrink over time, forcing the minimum distance between them to occur when the activities are completed. To ensure that the distance between A and B is at least 210vm, we should let the minimum distance be 210 m, which \(B_k\) can finish in \(210\div 30=7\)h. Therefore, the time lag needed to meet distance requirements is of the Finish-to-Finish type of minimum time lag between \(A_k\) and \(B_k\), that is, \(\hbox {FTF}_{A_kB_k}^{\min }(7)\), \(k=1,2,3\).

(2) For roadbed (B) and surface layer (C), the construction speeds of \(B_k\) and \(C_k\) are 30 m/h and 20vm/h, respectively. The faster \(B_k\) lies ahead of the slower \(C_k\). This means that the distance between them increases over time. Therefore, the minimum distance between them will occur when the activities begin. To ensure that the distance between B and C is at least 150 m, we should let the minimum distance be 150m, which \(B_k\) can finish in \(150\div 30=5\)h. Therefore, the time lag needed to meet distance requirements is of the Start-to-Start type of minimum time lag between \(B_k\) and \(C_k\), that is, \(\hbox {STS}_{B_kC_k}^{\min }(5)\). In addition, the roadbed (\(B_k\)) is a cement-stabilized structure that must be maintained for at least 7 h following cement stabilization. Thus, 5 h after the start time of \(B_k\), the minimum distance between \(B_k\) and \(C_k\) will be 150vm, but \(C_k\) must wait 7 h for “cement hardening.” Therefore, the start time of \(C_k\) is no earlier than \(5+7=12\) h after the start time of \(B_k\), that is, \(\hbox {STS}_{B_kC_k}^{\min }(12)\), \(k=1,2,3\).

Given the above, I list the precedence relations between activities in the project in Table 1.

Appendix B

Compared with CPM network, the biggest change of the AoN network with equivalent \(\hbox {STS}_{ij}^{\min }(w_{ij}^{\prime })\) is having arcs (ij) with negative lengths \(d_{ij}=w_{ij}^{\prime }<0\) which permits activity j earlier than activity i. This change may be the main reason for the singularities—the invisible consumptions and enlargements of activity floats. The analysis in Sect. 3.2 shows that the start time of the noncritical activity j will be fixed when the activity starts, which can be equivalently seen that the latest start time of the activity is brought forward to its actual start time. Equation (19) presents that for arc (ij), the latest start time of activity i may be determined by the latest start time of activity j, therefore the changing of the latest start time of activity j may affect the latest start time of activity i. Similarly, other activities’ latest start times determined by the latest start time of activity i also will be changed.

Suppose that t is the execution time of the project. Based on the analysis in Sect. 3.2, activity j has actually started at time \(s_j\le t\), which implies that its start time is no earlier and no later than \(s_j\). According to the types of GPRs, this case can be represented as a Begin-to-Start type of minimum and maximum time lags\(w_{sj}=s_j\) between the project and activity j, as follows: \(BTS_{sj}^{\min }(s_j)\) and \(BTS_{sj}^{\max }(s_j)\Leftrightarrow STB_{js}^{\min }(-s_j)\).

To represent \(BTS_{sj}^{\min }(s_j)\) and \(BTS_{js}^{\min }(-s_j)\), arc (sj) with length \(d_{sj}=w_{sj}=s_j\), and arc (js) with length \(d_{js}=w_{js}=-s_j\) should be added to the Bartusch AoN network. According to the computation of \(\hbox {ES}_j\), a path with length \(l=\hbox {ES}_j\) from the beginning node (s) to node (j) exists in the original network. Therefore, the path is equivalent to arc (sj) with length \(d_{sj}=w_{sj}=\hbox {ES}_j\), and only the addition of arc (js) with length \(d_{js}=w_{js}=-\hbox {ES}_j\) is required. If activity j consumed its free float by \(\Delta \hbox {FF}_j\), specifically, \(s_j=\hbox {ES}_j=\Delta \hbox {FF}_j\), \(BTS_{sj}^{\min }(s_j)\) and \(STB_{js}^{\min }(-s_j)\) should be added and represented. No path with length \(l=s_j\) probably exists from node (s) to node (j) in the original network. Therefore, arc (sj) with length \(d_{sj}=w_{sj}=s_j\) and arc (js) with length \(d_{js}=w_{js}=-s_j\) need to be added to the activity network. After adding the corresponding arcs for all activities j with \(\hbox {LS}_j\le \hbox {ES}_i<t<\hbox {LS}_j\) based on the described cases, the time parameters of activities, such as the latest start times of activities, may be changed and result in new activity floats different from the original values. The invisible consumptions and enlargements of time floats of activity j and other activities starting later than t can be obtained by computing the activity floats and comparing them with their original values.

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Su, Z. Invisible consumptions and enlargements of activity floats under generalized precedence relations. Soft Comput 23, 10837–10852 (2019). https://doi.org/10.1007/s00500-018-3637-4

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