Multiobjective Evolutionary Finance-Based Scheduling: Entire Projects’ Portfolio

Abstract

A strength Pareto evolutionary algorithm (SPEA) is proposed and was modified by incorporating logic-preserving crossover and mutation operators and employed to devise a set of optimum finance-based schedules of multiple projects being implemented simultaneously by a construction contractor. The problem involves the minimization of the conflicting objectives of financing costs, duration of the group of projects, and the required credit. The modified SPEA was employed to obtain the Pareto-optimal fronts for the two-objective combinations as well as the three objectives. In addition, a fuzzy-based technique was used to help the contractors select the best compromise solution over the Pareto-optimal solutions. The proposed approach has been developed and implemented on projects with different sizes. The results obtained by the modified SPEA, fuzzy-based approach demonstrated its potential and effectiveness in finance-based scheduling of multiple projects.