Optimizing time-cost in generalized construction projects using multiple-objective social group optimization and multi-criteria decision-making methods

摘要

Purpose Project managers work to ensure successful project completion within the shortest period and at the lowest cost. One of the main tasks of a project manager in the planning phase is to generate the project time-cost curve, and furthermore, to determine the most appropriate schedule for the construction process. Numerous existing time-cost tradeoff analysis models have focused on solving a simple project representation without regarding for typical activity and project characteristics. This study aims to present a novel approach called "multiple-objective social group optimization" (MOSGO) for optimizing time-cost decisions in generalized construction projects. Design/methodology/approach In this paper, a novel MOGSO to mimic the time-cost tradeoff problem in generalized construction projects is proposed. The MOSGO has slightly modified the mechanism operation from the original algorithm to be a free-parameter algorithm and to enhance the exploring and exploiting balance in an optimization algorithm. The evidential reasoning technique is used to rank the global optimal obtained non-dominated solutions to help decision makers reach a single compromise solution. Findings Two case studies of real construction projects were investigated and the performance of MOSGO was compared to those of widely considered multiple-objective evolutionary algorithms. The comparison results indicated that the MOSGO approach is a powerful, efficient and effective tool in finding the time-cost curve. In addition, the multi-criteria decision-making approaches were applied to identify the best schedule for project implementation.Social implications The proposal model can be applied to multi-objective contexts in diversified fields. Moreover, the model is also a useful reference for future research. Originality/value This paper makes contributions to extant literature by: introducing a method for making TCT models applicable to actual projects by considering general activity precedence relations; developing a novel MOSGO algorithm to solving TCT problems in multi-objective context by a single simulation; and facilitating the TCT problems to project managers by using multi-criteria decision-making approaches.