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Optimizing the scheduling of crew deployments in repetitive construction projects under uncertainty

Optimizing the scheduling of crew deployments in repetitive construction projects under uncertainty This paper presents the development of a novel model for optimizing the scheduling of crew deployments in repetitive construction projects while considering uncertainty in crew production rates.Design/methodology/approachThe model computations are performed in two modules: (1) simulation module that integrates Monte Carlo simulation and a resource-driven scheduling technique to calculate the earliest crew deployment dates for all activities that fully comply with crew work continuity while considering uncertainty; and (2) optimization module that utilizes genetic algorithms to search for and identify optimal crew deployment plans that provide optimal trade-offs between project duration and crew deployment plan cost.FindingsA real-life example of street renovation is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the stochastic scheduling of crew deployments in repetitive construction projects.Originality/valueThe original contribution of this research is creating a novel multiobjective stochastic scheduling optimization model for both serial and nonserial repetitive construction projects that is capable of identifying an optimal crew deployment plan that simultaneously minimizes project duration and crew deployment cost. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Engineering, Construction and Architectural Management Emerald Publishing

Optimizing the scheduling of crew deployments in repetitive construction projects under uncertainty

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0969-9988
DOI
10.1108/ecam-05-2020-0304
Publisher site
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Abstract

This paper presents the development of a novel model for optimizing the scheduling of crew deployments in repetitive construction projects while considering uncertainty in crew production rates.Design/methodology/approachThe model computations are performed in two modules: (1) simulation module that integrates Monte Carlo simulation and a resource-driven scheduling technique to calculate the earliest crew deployment dates for all activities that fully comply with crew work continuity while considering uncertainty; and (2) optimization module that utilizes genetic algorithms to search for and identify optimal crew deployment plans that provide optimal trade-offs between project duration and crew deployment plan cost.FindingsA real-life example of street renovation is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the stochastic scheduling of crew deployments in repetitive construction projects.Originality/valueThe original contribution of this research is creating a novel multiobjective stochastic scheduling optimization model for both serial and nonserial repetitive construction projects that is capable of identifying an optimal crew deployment plan that simultaneously minimizes project duration and crew deployment cost.

Journal

Engineering, Construction and Architectural Management – Emerald Publishing

Published: Jun 25, 2021

Keywords: Repetitive construction projects; Linear scheduling; Stochastic models; Monte Carlo simulation; Crew deployment date; Optimization; Genetic algorithms; Construction management

References

  • Causes of delay in building construction projects in Egypt
    Abd El-Razek, M.E.; Bassioni, H.A.; Mobarak, A.M.
  • Monte Carlo simulation to solve fuzzy dynamic fault tree*
    Abdo, H.; Flaus, J.M.
  • Probabilistic simulation studies for repetitive construction processes
    AbouRizk, S.M.; Halpin, D.W.
  • Statistical properties OF construction duration data
    Abourizk, S.M.; Halpin, D.W.
  • Minimizing duration and crew work interruptions of repetitive construction projects
    Altuwaim, A.; El-Rayes, K.
  • Causes of delay in large construction projects
    Assaf, S.A.; Al-Hejji, S.
  • Fuzzy dynamic programming for optimized scheduling of repetitive construction projects
    Bakry, I.; Moselhi, O.; Zayed, T.
  • Probabilistic estimation and allocation of project time contingency
    Barraza, G.a.
  • A fast and elitist multi-objective genetic algorithm: NSGAII
    Deb, K.; Pratap, A.; Agarwal, S.; Meyarivan, T.
  • Nondeterministic networking methods
    Diaz, C.F.; Hadipriono, F.C.
  • Linear scheduling model with varying production rates
    Duffy, G.A.; Oberlender, G.D.; Seok Jeong, D.H.
  • Scheduling repetitive construction projects using fuzzy linear programming
    El-kholy, A.
  • Resource driven scheduling of repetitive activities
    El-Rayes, K.; Moselhi, O.
  • Optimizing resource utilization for repetitive construction projects
    El-Rayes, K.; Moselhi, O.
  • Time-cost trade-off in repetitive projects with soft logic
    Fan, S.; Lin, Y.
  • DEAP: evolutionary algorithms made easy
    Fortin, F.A.; Rainville, F.M.D; Gardner, M.A.; Parizeau, M.; Gagn´e, C.
  • Hybrid approach for addressing uncertainty in risk assessments
    Guyonnet, D.; Bourgine, B.; Dubois, D.; Fargier, H.; Côme, B.; Chilès, J.P.P.; Côme, B.; Chilès, J.P.P.
  • Efficient repetitive scheduling for high-rise construction
    Hegazy, T.; Kamarah, E.
  • Cost optimization in projects with repetitive nonserial activities
    Hegazy, T.; Wassef, N.
  • Optimal planning and scheduling for repetitive construction projects
    Hyari, K.; El-Rayes, K.
  • Automated trade-off between time and cost in planning repetitive construction projects
    Hyari, K.H.; El-Rayes, K.; El-Mashaleh, M.
  • Sequence step algorithm for continuous resource utilization in probabilistic repetitive projects
    Ioannou, P.G.; Srisuwanrat, C.
  • Optimizing the utilization of multiple labor shifts in construction projects
    Jun, D.H.; El-Rayes, K.
  • Siren: a repetitive construction simulation model
    Kavanagh, D.P.
  • Probability of project completion using stochastic project scheduling simulation
    Lee, D.E.
  • Optimization model for resource assignment problems of linear construction projects
    Liu, S.S.; Wang, C.J.
  • Two-stage profit optimization model for linear scheduling problems considering cash flow
    Liu, S.S.; Wang, C.J.
  • A genetic algorithm-based method for scheduling repetitive construction projects
    Long, L.D.; Ohsato, A.
  • Large construction projects in developing countries: a case study from Vietnam
    Long, N.D.; Ogunlana, S.; Quang, T.; Lam, K.C.
  • Fuzzy repetitive scheduling method for projects with repeating activities
    Maravas, A.; Pantouvakis, J.-P.
  • Least cost scheduling for repetitive projects
    Moselhi, O.; El-Rayes, K.
  • Scheduling of repetitive projects with cost optimization
    Moselhi, O.; El-Rayes, K.
  • Accelerating repetitive construction projects: with uncertainty and contractors' judgment
    Moselhi, O.; Bakry, I.; Alshibani, A.
  • Fuzzy Monte Carlo simulation and risk assessment in construction
    Sadeghi, N.; Fayek, A.R.; Pedrycz, W.
  • Optimizing the planning of construction site security for critical infrastructure projects
    Said, H.; El-Rayes, K.
  • Float consumption impact on cost and schedule in the construction industry
    Sakka, Z.I.; El-Sayegh, S.M.
  • Optimal scheduling of probabilistic repetitive projects using completed unit and genetic algorithms
    Srisuwanrat, C.; Ioannou, P.G.
  • Delay risk assessment of repetitive construction projects using line-of-balance scheduling and Monte Carlo simulation
    Tokdemir, O.B.; Erol, H.; Dikmen, I.
  • Problems causing delays in major construction projects in Thailand
    Toor, S.U.R.; Ogunlana, S.
  • Work continuity constraints in project scheduling
    Vanhoucke, M.
  • Stochastic resource-constrained scheduling for repetitive construction projects with uncertain supply of resources and funding
    Yang, I.T.; Chang, C.Y.