Fuzzy-multi-objective particle swarm optimization for time–cost–quality tradeoff in construction

The time–cost–quality tradeoff (TCQT) problem is to decide an optimal combination of construction methods with the objective of minimizing cost and time while maximizing quality. Searching for such an optimal combination of construction methods needs to evaluate the total cost, time and quality of the project. These performances, especially the quality, may be collected and recorded in terms of imprecise or vague data rather than precise numbers. This paper presents a fuzzy-multi-objective particle swarm optimization to solve the fuzzy TCQT problem. The time, cost and quality are described by fuzzy numbers and a fuzzy multi-attribute utility methodology incorporated with constrained fuzzy arithmetic operations is adopted to evaluate the selected construction methods. The particle swarm optimization is applied to search for the TCQT solutions by incorporating the fuzzy multi-attribute utility methodology. The proposed methodology is implemented and justified through computational analyses. The study is expected to provide an alternative methodology for solving the time–cost–quality tradeoff problem.

Research highlights
► Tim–cost–quality tradeoff problems in construction planning are addressed.
► Fuzzy numbers are used to describe the time, cost and quality.
► Constrained fuzzy arithmetic operations are particularly proposed.
► Particle swarm optimization is applied to solve the fuzzy TCQT problemst.
► Fuzzy multi-attribute utility is used to evaluate solutions for fuzzy TCQT problems.