Critical Sequence Crashing Heuristic for Resource-Constrained Discrete Time-Cost Trade-Off Problem

SÖNMEZ R., Iranagh M. A., Uysal F.

JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, cilt.142, sa.3, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 142 Sayı: 3
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1061/(asce)co.1943-7862.0001077
  • Dergi Adı: JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: Project management, Resource management, Construction planning, Scheduling, Costs, Optimization, Cost and schedule, PARTICLE SWARM OPTIMIZATION, PROJECT SCHEDULING PROBLEM, GENETIC ALGORITHM, CONSTRUCTION TIME, MANAGEMENT, JUSTIFICATION, ALLOCATION, SCHEMES
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Despite the importance of project deadlines and resource constraints in construction scheduling, very little success has been achieved in solving the resource-constrained discrete time-cost trade-off problem (RCDTCTP), especially for large-scale projects. In this paper a new heuristic method is designed and developed to achieve fast and high-quality solutions for the large-scale RCDTCTP. The proposed method is based on the novel principles to enable effective exploration of the search space through adequate selection of the activities to be crashed for a resource constrained schedule, by only crashing the activities with zero float in a resource constrained-schedule, which form the critical sequence. The computational experiment results reveal that the new critical sequence crashing heuristic outperforms the state-of-the-art methods, both in terms of the solution quality concerning project cost and computation time. Solutions with a deviation of 0.25% from the best known solutions are achieved within seconds for the first time, for a large-scale project including up to 2,000 activities. The main contribution of the new heuristic to practitioners and researchers is that it provides a fast and effective method for optimal scheduling of real-life-size construction projects with project deadlines and resource constraints. (C) 2015 American Society of Civil Engineers.