MOSCOPEA: Multi-objective construction scheduling optimization using elitist non-dominated sorting genetic algorithm

Mohammed S. El-Abbasy, Ashraf Elazouni, Tarek Zayed

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

Managing multiple construction projects simultaneously involves sharing and allocating different types of resources, including cash, equipment, and manpower among different concurrent projects. Moreover, ensuring the availability of cash throughout the multiple projects' execution period increases the scheduling complexity. Accordingly, this paper presents the development of an automated system that optimizes the scheduling of multiple construction projects with respect to multiple objectives considering both financial and resource aspects under a single platform. The automated system is named Multi-Objective SCheduling OPtimization using Evolutionary Algorithm (MOSCOPEA). The system aims to help contractors in devising schedules that obtain optimal tradeoffs between different projects' objectives, namely: duration of multiple projects, total cost, financing cost, maximum required credit, profit, and resource fluctuations and peak demand. Moreover, it offers the flexibility in selecting the desired set of objectives to be optimized together. Finally, the developed system is tested and implemented using different case studies of different project sizes obtained from literature to demonstrate its capabilities in scheduling optimization.
Original languageEnglish
Pages (from-to)153-170
Number of pages18
JournalAutomation in Construction
Volume71
Issue numberPart 2
DOIs
Publication statusPublished - 1 Nov 2016
Externally publishedYes

Keywords

  • Automated system
  • Cash flow management
  • Evolutionary algorithm
  • Multi-objective optimization
  • Resource management
  • Scheduling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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