Efficient multi-objective optimization algorithms for construction site layout problem

Construction site layout planning is one of the managerial aspects of the construction industry and has significant impacts on performance of the sites. Since in real site layout optimization, many objectives are involved, therefore multi-objective algorithms are needed. In this study, multi-objective version of two meta-heuristics, CBO and ECBO, are developed and their applicability and performance are checked on a case study. The quality of the results obtained, verify the ability of these algorithms in finding optimal pareto front on this problem. Another tool that is utilized in this study is data envelopment analysis (DEA) which by calculating the efficiency of optimal pareto front layouts, can help decision makers to select the final layout among the candidates. It should be mentioned that the DEA has previously been used in models with multiple inputs and outputs.

[1]  Ali Kaveh,et al.  Applications of Metaheuristic Optimization Algorithms in Civil Engineering , 2016 .

[2]  Mostafa Khanzadi,et al.  Construction Site Layout Planning Problem Using Two New Meta-heuristic Algorithms , 2016 .

[3]  David Rey,et al.  A multi-objective mixed integer nonlinear programming model for construction site layout planning to minimise noise pollution and transport costs , 2016 .

[4]  Ali Kaveh,et al.  AN ADAPTED HARMONY SEARCH BASED ALGORITHM FOR FACILITY LAYOUT OPTIMIZATION , 2012 .

[5]  Ka Chi Lam,et al.  The application of the ant colony optimization algorithm to the construction site layout planning problem , 2007 .

[6]  A. Kaveh,et al.  Enhanced colliding bodies optimization for design problems with continuous and discrete variables , 2014, Adv. Eng. Softw..

[7]  Sai On Cheung,et al.  Site pre-cast yard layout arrangement through genetic algorithms , 2002 .

[8]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[9]  Ka Chi Lam,et al.  Application of the entropy technique and genetic algorithms to construction site layout planning of medium‐size projects , 2005 .

[10]  Iris D. Tommelein,et al.  SightPlan Model for Site Layout , 1992 .

[11]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[12]  Ali Kaveh,et al.  Advances in Metaheuristic Algorithms for Optimal Design of Structures , 2014 .

[13]  C. M. Tam,et al.  Genetic Algorithm for Optimizing Supply Locations around Tower Crane , 2001 .

[14]  Mohsen Andayesh,et al.  The constructs of site layout modeling: an overview , 2015 .

[15]  Ka Chi Lam,et al.  A decision-making system for construction site layout planning , 2011 .

[16]  Khaled A El-Rayes,et al.  Trade-off between Safety and Cost in Planning Construction Site Layouts , 2005 .

[17]  Hong Zhang,et al.  Particle Swarm Optimization for Construction Site Unequal-Area Layout , 2008 .

[18]  Ali Azadeh,et al.  A new approach for layout optimization in maintenance workshops with safety factors: The case of a gas transmission unit , 2013 .

[19]  Gulben Calis,et al.  An Improved Ant Colony Optimization Algorithm for Construction Site Layout Problems , 2015 .

[20]  Min-Yuan Cheng,et al.  A hybrid swarm intelligence based particle-bee algorithm for construction site layout optimization , 2012, Expert Syst. Appl..

[21]  M. P. Saka,et al.  Construction site layout planning using multi-objective artificial bee colony algorithm with Levy flights , 2014 .

[22]  Amalia Utamima,et al.  A comparative study of GA, PSO and ACO for solving construction site layout optimization , 2015 .

[23]  Jiuping Xu,et al.  Multi-Objective Dynamic Construction Site Layout Planning in Fuzzy Random Environment , 2012 .

[24]  I-Cheng Yeh,et al.  Architectural layout optimization using annealed neural network , 2006 .

[25]  Ali Kaveh,et al.  Colliding bodies optimization: A novel meta-heuristic method , 2014 .

[26]  Peter E.D. Love,et al.  Genetic search for solving construction site-level unequal-area facility layout problems , 2000 .