Using elitist particle swarm optimization to facilitate bicriterion time-cost trade-off analysis

作者：Yang I Tung^*

来源：Journal of Construction Engineering and Management-ASCE, 2007, 133(7): 498-505.

DOI：10.1061/(ASCE)0733-9364(2007)133:7(498)

The present study develops a new optimization algorithm to find the complete time-cost profile (Pareto front) over a set of feasible project durations, i.e., it solves the time-cost trade-off problem. To improve existing methods, the proposed algorithm aims to achieve three goals: (1) to obtain the entire Pareto front in a single run; (2) to be insensitive to the scales of time and cost; and (3) to treat all existing types of activity time-cost functions, such as linear, nonlinear, discrete, discontinuous, and a hybrid of the above. The proposed algorithm modifies a population-based search procedure, particle swarm optimization, by adopting an elite archiving scheme to store nondominated solutions and by aptly using members of the archive to direct further search. Through a fast food outlet example, the proposed algorithm is shown effective and efficient in conducting advanced bicriterion time-cost analysis. Future applications of the proposed algorithm are suggested in the conclusion.

• 出版日期2007-7