Dynamic Postponement in Off-Site/On-Site Construction Operations in the Face of On-Site Disruptions

Off-site construction operations can be subject to downstream construction site disruptions. These disruptions - such as forecasted high wind conditions which will limit on-site crane movements for example - delay on-site construction and impact on the effectiveness of the off-site production of construction modules. In this paper we propose a new disruption management strategy of Dynamic Postponement. Simulation Based Optimisation by use of a Genetic Algorithm is used to determine the optimal balance between on/off-site work to maximise performance. This method is applied to an industrial case study. Finally, an outline of how Dynamic Postponement can be treated as an agent based system is provided.

[1]  Mohamed Al-Hussein,et al.  Simulation based multi-objective cost-time trade-off for multi-family residential off-site construction , 2015, 2015 Winter Simulation Conference (WSC).

[2]  Andrew R.J. Dainty,et al.  Perspectives of UK housebuilders on the use of offsite modern methods of construction , 2007 .

[3]  Paul Syms,et al.  Modern methods of construction , 2009 .

[4]  Angel A. Juan,et al.  A simheuristic algorithm for solving the permutation flow shop problem with stochastic processing times , 2014, Simul. Model. Pract. Theory.

[5]  Bhanu S. Ragu-Nathan,et al.  The impact of supply chain management practices on competitive advantage and organizational performance , 2006 .

[6]  Mehrdad Arashpour,et al.  Optimization of process integration and multi-skilled resource utilization in off-site construction , 2015 .

[7]  James T. O'Connor,et al.  Industrial Project Execution Planning: Modularization versus Stick-Built , 2016 .

[8]  Mehrdad Arashpour,et al.  Off-site construction optimization: sequencing multiple job classes with time constraints , 2016 .

[9]  E. Zavadskas,et al.  Critical evaluation of off-site construction research: a scientometric analysis , 2018 .

[10]  Chandrasekharan Rajendran,et al.  A multiobjective genetic algorithm for scheduling a flexible manufacturing system , 2003 .

[11]  Reha Uzsoy,et al.  Executing production schedules in the face of uncertainties: A review and some future directions , 2005, Eur. J. Oper. Res..

[12]  Simaan M. AbouRizk,et al.  Off-Site Construction Planning Using Discrete Event Simulation , 2012 .

[13]  Jose M. Framiñan,et al.  Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective , 2010, Comput. Oper. Res..

[14]  Joseph Geunes,et al.  Predictive-reactive scheduling on a single resource with uncertain future jobs , 2008, Eur. J. Oper. Res..

[15]  Mehrdad Arashpour,et al.  Optimal process integration architectures in off-site construction: Theorizing the use of multi-skilled resources , 2018 .

[16]  U.k. Shivastava,et al.  Quantitative Techniques For Managerial Decisions , 1986 .

[17]  Julio C. Martinez.  Methodology for Conducting Discrete-Event Simulation Studies in Construction Engineering and Management , 2010 .

[18]  Nashwan Dawood,et al.  Simulation-based genetic algorithms for construction supply chain management: Off-site precast concrete production as a case study , 2012, OR Insight.

[19]  John Meiling,et al.  Defects in offsite construction: timber module prefabrication , 2009 .

[20]  Washington Y. Ochieng,et al.  A Multi-Objective GA-based Optimisation for Holistic Manufacturing,transportation and Assembly of Precast Construction , 2016 .