Genetic algorithm optimization for dynamic construction site layout planning

The dynamic construction site layout planning (DCSLP) problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic optimization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as safety and environmental considerations resulting from facilities’ operations and interconnections. The latter considerations are taken into account in the form of preferences or constraints regarding the proximity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP (for Nondeterministic Polynomial time)- hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. Several case studies and operational scenarios have been implemented through the Palisade’s Evolver software for model testing and evaluation. The results indicate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desirable preferences or constraints in the decision process

Cuckoo search algorithm for construction site layout planning

A novel metaheuristic optimization algorithm based on cuckoo search algorithm (CSA) is presented to solve the construction site layout planning problem (CSLP). CSLP is a complex optimization problem with various applications, such as plant layout, construction site layout, and computer chip layout. Many researchers have investigated the CSLP by applying many algorithms in an exact or heuristic approach. Although both methods yield a promising result, technically, nature-inspired algorithms demonstrate high achievement in successful percentage. In the last two decades, researchers have been developing a new nature-inspired algorithm for solving different types of optimization problems. The CSA has gained popularity in resolving large and complex issues with promising results compared with other nature-inspired algorithms. However, for solving CSLP, the algorithm based on CSA is still minor. Thus, this study proposed CSA with additional modification in the algorithm mechanism, where the algorithm shows a promising result and can solve CSLP cases.publishedVersionPeer reviewe

Genetic Algorithm–Simulation Framework for Decision Making in Construction Site Layout Planning

Site layout planning is a complicated task in many construction projects because of the diversity of decision variables, conflicting objectives, and the variety of possible solutions. This paper describes a framework that facilitates decision making on site-layout planning problems. The framework consists of three phases: (1) functionality evaluation phase (FEP), which qualitatively evaluates using a new method; (2) cost evaluation phase (CEP), which quantitatively evaluates the goodness of the layouts using simulation; and (3) value evaluation phase (VEP), which selects the most desirable layout from both qualitative and quantitative aspects. This framework also takes advantage of heuristic optimization through genetic algorithm (GA) to search for the most qualified layouts within FEP. The primary contribution of this research is to introduce a novel method for evaluating quality of layouts, which more realistically model the closeness constraints, and consider size and location desirability in the evaluating function. Also, using simulation for estimating project cost improves the effectiveness of the framework in practice because simulation can model construction processes, uncertainties, resources, and dynamic interactions between various parameters. Applicability of the framework is demonstrated through a case study of the layout planning of a tunneling project

Charged System Search and Magnetic Charged System Search Algorithms for Construction Site Layout Planning Optimization

Construction site layout planning can be considered as an effort to place different temporary facilities in available site locations such that multiple objectives are satisfied as much as possible. With the extension of high-rise building construction and construction activities besides the lack of available spaces in construction sites, proper utilization of this resource has been highlighted because of its significant positive influences on direct cost, safety, and security of the site which consequently affects the total cost and schedule of the project. Thus the construction site layout planning is considered as one of the essential and important phases in construction projects. Site layout planning problem is an NP-Hard problem from the viewpoint of complexity. In this research, two prominent meta-heuristic algorithms, namely Charged System Search (CSS) and Magnetic Charged System Search (MCSS) are utilized to optimize the site layout planning problem. The obtained results of implementing these two algorithms for two different types of site space modeling are compared with the results of the Particle Swarm Optimization (PSO) algorithm and also those of the previous studies. The results illustrate the capability of the CSS and MCSS algorithms in solving the present problem

Construction Site Layout Planning Using a Simulation-Based Decision Support Tool

Background: Site layout plan is one of the important decisions to be made in the planning phase of each construction project as it can significantly impact on-site transportation, construction logistics and safety. This decision could be complicated due to the uncertainties inherent in construction projects and the complex relationships between the influencing factors and decision variables. Methods: To improve site layout planning, this study aims to develop a simulation-based decision support tool (DST) that enables planners to consider: 1) construction uncertainties, 2) construction resources (i.e., material, equipment and workers), 3) site layout constraints, and 4) mutual impacts between site layout and construction plan variables, for site layout planning of construction projects. Results: The developed DST visualizes the site layout plan within a simulation environment, and provides seamless interactions between the site layout model and the simulation model. These capabilities facilitate planning construction site layout using simulation by establishing two-way information flows between the site layout and simulation components, which can further promote application of simulation in construction site layout planning. Usefulness and practicality of the proposed DST is demonstrated in site layout planning of a steel erection project. Conclusions: Using this DST can reduce some common wastes in construction projects and the cost associated with them, including on-site transportation, material handling and storage, and waiting time for the material arrival

Application of a hybrid MCDM method in construction logistics

L

A hybrid simulation approach for quantitatively analyzing the impact of facility size on construction projects

Sizing temporary facilities is a crucial task in construction site layout planning due to its significant impact on project productivity and cost. This paper describes a simulation-based approach for modeling the size of facilities that temporarily contain materials in construction projects. Different methods have been introduced for estimating the required size of this kind of facility; however, space limitations, particularly on congested sites, may not allow the planner to allocate the estimated space to the facilities. This study aims at quantitatively analyzing the impact of facility size on the project and modeling the managerial corrective actions to remedy the space shortage in facilities. To this end, a hybrid discrete-continuous simulation technique is adopted. Simulation is superior in modeling dynamic interactions between variables as well as modeling construction processes with inherent uncertainties. The combination of discrete and continuous simulation is used to enhance accuracy and model the project at both operational level (i.e., activity level with higher level of detail) to estimate production rate, and strategic level (i.e., macro level with lower level of detail) to account for some construction planning decisions such as material management variables. The novelty of this study is analyzing the impact of facility size on the project time and cost, while managerial actions taken to resolve space shortages are modeled, and interdependent influencing parameters of the different disciplines, such as site layout, material management, logistics, and construction process planning are integrated in a unified model. The applicability and suitability of the proposed approach is demonstrated in layout planning of a tunneling project site

An integrated simulation model for site layout planning of tunnelling projects

Overlooking site layout in the planning phase of construction projects leads to loss of productivity and incurs extra costs. In tunneling projects, site layout has a significant impact on material flow and tunneling operations, particularly on congested sites. In addition, construction planning decisions can influence the efficiency of the layout. This paper proposes simulation as a decision making tool to model tunnel construction operations and site layout, and capture their mutual influences. To facilitate building the simulation model, even for users with limited simulation knowledge, a special purpose simulation (SPS) tool was customized and developed. This simulation tool provides an integrated environment to model the parameters of different disciplines including site layout, material procurement, tunnel operations and logistics. The developed tool is of great assistance for the planners to make decisions simultaneously on site layout and other construction planning parameters, and find the most cost-efficient plan