A Multi-Objective Optimization Approach for the Cost-Time-Quality Trade-off in Construction Projects
DOI:
https://doi.org/10.19255/JMPM02713Keywords:
Project Control, triple constraints, Multi Objective Optimization, Non-dominated Sorting Genetic AlgorithmsAbstract
The project management triangle is described as the factors of time, cost, and quality of a project. These triple constraints are considered part of the major tangible criteria for determining the success of a project (Joslin and Müller 2016; Kabirifar and Mojtahedi 2019). In order to maintain a successful standing for a project, constant monitoring and modification is done to these three factors throughout a project’s lifetime. However, modifying one factor has effects on other factors which is a trade-off that many construction projects struggle with (Van Wyngaard et al. 2011). This trade-off can have a considerable measure of negative impacts on the project by diminishing the quality, and increasing the actual duration or incurred costs. Hence, project managers and planners must put a considerable amount of effort in ensuring suitable valuation of the variables which effect those factors. Although many studies have been conducted on the optimization of time, cost, and quality, most of them fail to address some of the main components of the triple constraints such as labor allocation, productivity, and quality. Additionally, managing the quality of a project is done during the construction phase rather than the planning phase which can have tremendous effects on the final quality of the project (Aljassmi and Abduljalil, 2018). The primary aim of this paper is to present a functional model of time, cost, and quality trade-off optimization while taking into consideration the effects and values of variables such as labor count, productivity, and quality through the use of Multi Objective Optimization (MOO) and Non-dominated Sorting Genetic Algorithms (NSGA II). This function model will provide a set of optimal solutions and hence provide decision makers with tools to analyse the state of the project and take actions suiting the project requirements. To demonstrate the effectivity and capabilities of the model, an example from previous literature is analysed to present and visualize several optimal solutions to the variables and trade-off of the time, cost, and quality functions.
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