Solving large-scale discrete time-cost trade-off problem using hybrid multi-verse optimizer model

The analysis of the relationship between time and cost is a crucial aspect of construction project management. Various optimization techniques have been developed to solve time-cost trade-off problems. A hybrid multi-verse optimizer model (hDMVO) is introduced in this study, which combines the multi-verse optimizer (MVO) and the sine cosine algorithm (SCA) to address the discrete time-cost trade-off problem (DTCTP). The algorithm's optimality is evaluated by using 23 well-known benchmark test functions. The results demonstrate that hDMVO is competitive with MVO, SCA, the dragonfly algorithm and ant lion optimization. The performance of hDMVO is evaluated using four benchmark test problems of DTCTP, including two medium-scale instances (63 activities) and two large-scale instances (630 activities). The results indicate that hDMVO can provide superior solutions in the time-cost optimization of large-scale and complex projects compared to previous algorithms.

Automated summary

The study introduces a hybrid multi-verse optimizer model (hDMVO) that combines the multi-verse optimizer (MVO) and the sine cosine algorithm (SCA) to solve the discrete time-cost trade-off problem (DTCTP). The optimality of the algorithm is evaluated using 23 benchmark test functions, demonstrating its competitiveness with other algorithms. The performance of hDMVO is further evaluated using four benchmark test problems, showing its superiority in time-cost optimization for large-scale and complex projects compared to previous algorithms.