Multi-Objective Simultaneous Optimization for Linear Projects Scheduling


Scheduling linear projects requires an optimization tool that does not only minimizes project duration and cost, but also maximizes the utilization of crews, accounts for travelling distance between units, and meets the delivery dates of the project's units. This paper presents a multi-objective optimization model for scheduling linear projects through developing set of non-dominated optimal schedules. The proposed model consists of: (1) a resource driven scheduling module accounting for heterogeneity among construction crews, and (2) an evolutionary optimization module via genetics algorithms (GAs) and Pareto front sorting (PFS) that searches the solution space for optimal schedules. The model is tested on a case study drawn from the literature and provided significantly better results compared to some of the well-recognized scheduling models. The proposed model is coded using Visual Basics for Applications on a commercial scheduling tool and can be easily adopted by practitioners to provide a broad-spectrum of optimal schedules.

Meeting Name

ASCE International Conference on Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience, i3CE 2019 (2019: Jun. 17-19, Atlanta, GA)


Civil, Architectural and Environmental Engineering

Keywords and Phrases

Information theory; Scheduling; Visualization, Construction crews; Driven scheduling; Evolutionary optimizations; Genetics algorithms; Multi-objective optimization models; Optimization tools; Scheduling models; Simultaneous optimization, Multiobjective optimization

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version


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© 2019 American Society of Civil Engineers (ASCE), All rights reserved.

Publication Date

01 Jun 2019