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Development of Multi-Objective Scheduling Model for Construction Projects Using Opposition-Based NSGA III

By: Sharma, Kamal.
Contributor(s): Trivedi, M. K.
Publisher: New York Springer 2021Edition: Vol.102(2), June.Description: 421-434p.Subject(s): Civil EngineeringOnline resources: Click here In: Journal of the institution of engineers (India): Series ASummary: With the aim of successfully completing the construction projects, several multi-objective scheduling models (MOSMs) have been systematically developed so far. In order to alleviate the limitations of existing MOSMs, in this paper, a multi-objective scheduling model is developed as an opposition-based non-dominated sorting genetic algorithm III (OBNSGA III). The developed model employs opposition-based learning technique in NSGA III that uses opposition numbers to generate the well diverse initial population and for generation jumping. The working efficiency of developed model is demonstrated through solving a time–cost-resources-quality trade-off optimization problem of a case study project that provides a set of Pareto-optimal solutions. The paper considers that each activity has several execution modes, which are accompanied by different amount of time, cost, resources and impact on entire project quality. Based on the performance metrics, hypothesis testing and results of developed model, the comparison between developed model and those reported in literature demonstrates the usefulness of developed model in simultaneous optimization of four objectives. Besides, outcomes of the proposed model, a value path plot to visualize more than three objectives, and a priori approach to select one solution from obtained Pareto-optimal solutions makes this paper useful to researchers and construction managers.
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With the aim of successfully completing the construction projects, several multi-objective scheduling models (MOSMs) have been systematically developed so far. In order to alleviate the limitations of existing MOSMs, in this paper, a multi-objective scheduling model is developed as an opposition-based non-dominated sorting genetic algorithm III (OBNSGA III). The developed model employs opposition-based learning technique in NSGA III that uses opposition numbers to generate the well diverse initial population and for generation jumping. The working efficiency of developed model is demonstrated through solving a time–cost-resources-quality trade-off optimization problem of a case study project that provides a set of Pareto-optimal solutions. The paper considers that each activity has several execution modes, which are accompanied by different amount of time, cost, resources and impact on entire project quality. Based on the performance metrics, hypothesis testing and results of developed model, the comparison between developed model and those reported in literature demonstrates the usefulness of developed model in simultaneous optimization of four objectives. Besides, outcomes of the proposed model, a value path plot to visualize more than three objectives, and a priori approach to select one solution from obtained Pareto-optimal solutions makes this paper useful to researchers and construction managers.

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