Pareto oriented optimization of discrete time cost trade off problem using particle swarm optimization

Date

2015-09-07

Author

Aminbakhsh, Saman
Sönmez, Rifat

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In project scheduling, it is feasible to reduce the duration of a project by allocating additional resources to its activities. However, crashing the project schedule will impose additional costs. Numerous research has focused on optimizing the trade-off between time and cost to achieve a set of non-dominated solutions. However, the majority of the research on time-cost trade-off problem developed methods for relatively simple problems including up to eighteen activities, which are not representing the complexity of real-life construction projects. In this work a Particle Swarm Optimization (PSO) technique is presented for Pareto oriented optimization of the complex discrete time-cost trade-off problems. The proposed PSO engages novel principles for representation and position-updating of the particles. The performance of the PSO is compared to the existing methods using a well-known 18-activity benchmark problem. A 63-activity problem is also included in computational experiments to validate the efficiency and effectiveness of the proposed PSO for a more complex problem. The results indicate that the proposed method provides a powerful alternative for the Pareto front optimization of DTCTPs.

Subject Keywords

Pareto front, Particle swarm optimization, Project scheduling, Time-cost trade-off problem

URI

http://www.arcom.ac.uk/-docs/proceedings/a2604506123225031831e79ce484fe5d.pdf
https://hdl.handle.net/11511/72547

Conference Name

31st Annual Association of Researchers in Construction Management Conference (7 - 9 Eylül 2015)

Collections

Department of Civil Engineering, Conference / Seminar

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Citation Formats

S. Aminbakhsh and R. Sönmez, “Pareto oriented optimization of discrete time cost trade off problem using particle swarm optimization,” Lincoln, United Kingdom, 2015, p. 33, Accessed: 00, 2021. [Online]. Available: http://www.arcom.ac.uk/-docs/proceedings/a2604506123225031831e79ce484fe5d.pdf.