Time-Cost Trade-Off Optimization with a New Initial Population Approach


TEKNIK DERGI, vol.30, no.6, pp.9561-9580, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 6
  • Publication Date: 2019
  • Doi Number: 10.18400/tekderg.410934
  • Journal Name: TEKNIK DERGI
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.9561-9580
  • Keywords: Construction project, time-cost trade-off problem, multi-objective optimization, metaheuristic algorithm, LEARNING-BASED OPTIMIZATION, PARTICLE SWARM OPTIMIZATION, GENETIC ALGORITHM, MULTIOBJECTIVE OPTIMIZATION, CONSTRUCTION TIME, DESIGN
  • Karadeniz Technical University Affiliated: Yes


Completion of a project on time is crucial for its stakeholders when the competitive environment in all industries is considered. This favorable target is achieved by finding the optimal set of time-cost alternatives, which is known as time-cost trade-off problem (TCTP) in the literature. In this study, a new initial population approach is presented to improve the quality of the optimal set of time-cost alternatives. It employs a predefined number of solutions to the single objective TCTP into the initial population of teaching learning-based algorithm, which is an optimizer for the multi-objective optimization of TCTP. Hence, it is aimed at descending randomness on the initial population and decreasing searching effort to catch the optimal set of time-cost alternatives in the search space. The proposed methodology is tested on a series of benchmark problems and the solutions obtained are compared with those available in the technical literature. Results show that the present method can produce favorable solutions as effective as other techniques applied for simultaneous optimization of TCTPs.