PurposeThis paper aims to present an integrated method for optimized project duration and costs, considering the size and cost of crews assigned to project activities' execution modes.Design/methodology/approachThe proposed method utilizes fuzzy set theory (FSs) for modeling uncertainties associated with activities' duration and cost and genetic algorithm (GA) for optimizing project schedule. The method has four main modules that support two optimization methods: modeling uncertainty and defuzzification module; scheduling module; cost calculations module; and decision-support module. The first optimization method uses the elitist non-dominated sorting genetic algorithm (NSGA-II), while the second uses a dynamic weighted optimization genetic algorithm. The developed scheduling and optimization methods are coded in python as a stand-alone automated computerized tool to facilitate the developed method's application.FindingsThe developed method is applied to a numerical example to demonstrate its use and illustrate its capabilities. The method was validated using a multi-layered comparative analysis that involves performance evaluation, statistical comparisons and stability evaluation. Results indicated that NSGA-II outperformed the weighted optimization method, resulting in a better global optimum solution, which avoided local minima entrapment. Moreover, the developed method was constructed under a deterministic scenario to evaluate its performance in finding optimal solutions against the previously developed literature methods. Results showed the developed method's superiority in finding a better optimal set of solutions in a reasonable processing time.Originality/valueThe novelty of the proposed method lies in its capacity to consider resource planning and project scheduling under uncertainty simultaneously while accounting for activity splitting.
In the course of a construction project, the project manager’s task is to ensure timely and cost-effective execution of the job. However, it is common that delays and over-budgeting to be experienced during the project execution. This schedule acceleration requires resource planning to account for the project’s limited resources. Therefore, this study proposes an integrated method that allows for joint consideration of project scheduling and resource planning while accounting for activity splitting. The objective is to determine the project’s optimal cost and duration while considering some input parameters such as the crew’s size and project’s activities’ cost and duration. The proposed method utilized the Genetic Algorithm (GA) to optimize the project duration and cost. Accordingly, the Weighted Sum was used as a multi-criteria decision support method to choose an optimal solution from the optimization results. The developed scheduling and optimization method is coded in Python as a stand-alone, automated, computerized tool to facilitate its application. A numerical example, utilizing the developed method, is employed to show the method’s robustness and assess its performance against other previously developed methods. Results indicated the developed method’s dominance in finding optimal solutions in a reasonable time avoiding local minima entrapment.
Multi-criteria decision making (MCDM) on energy-efficient buildings has become essential in both the industry and academia as construction projects grow increasingly complex. With a prime goal of increasing its effectiveness, MCDM research has witnessed tremendous growth over the past three decades. Despite the necessity to monitor the research growth of a research topic to identify its trends and gaps, and hence shed light on research areas that warrant future research attention, there is a lack of systematic literature analysis in MCDM area. To fill this gap, this paper recruited a mixed-review method of scientometric and systematic reviews of 56 research papers on seven selected popular MCDM techniques published from 2010 to March 2021. The scientometric review identified the most prolific journals, keyword correlations, and geospatial connections between research countries in the MCDM area. On the other hand, the systematic review analysis showed that there are five main research topics in MCDM. Furthermore, the major approaches applied in MCDM research were investigated.
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