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A platform for research: civil engineering, architecture and urbanism
MOSCOPEA: Multi-objective construction scheduling optimization using elitist non-dominated sorting genetic algorithm
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.
Highlights A multi-objective scheduling optimization system is developed. The system considers both financial and resource aspects under a single platform. The system allows selecting the desired set of objectives to be optimized together. The system can optimize different construction management scheduling problems. The system is tested and implemented using several case studies for demonstration.
MOSCOPEA: Multi-objective construction scheduling optimization using elitist non-dominated sorting genetic algorithm
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.
Highlights A multi-objective scheduling optimization system is developed. The system considers both financial and resource aspects under a single platform. The system allows selecting the desired set of objectives to be optimized together. The system can optimize different construction management scheduling problems. The system is tested and implemented using several case studies for demonstration.
MOSCOPEA: Multi-objective construction scheduling optimization using elitist non-dominated sorting genetic algorithm
El-Abbasy, Mohammed S. (author) / Elazouni, Ashraf (author) / Zayed, Tarek (author)
Automation in Construction ; 71 ; 153-170
2016-08-21
18 pages
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2016
| British Library Online Contents | 2011