Multiobjective evolutionary finance-based scheduling: Individual projects within a portfolio

Under cash-constrained conditions, the fulfillment of cash demands of the ongoing projects within a contractor's portfolio constitutes a set of conflicting objectives. As the profit values of the individual projects are maximized should their cash demands be fulfilled, the profit values of the individual projects constitute a set of multiple conflicting objectives. A Strength Pareto Evolutionary Algorithm (SPEA) employing a logic-preserving crossover and mutation operators is developed to devise Pareto-optimal finance-based schedules of multiple projects. The Pareto-optimal solutions allow the decision makers select the best solution based on their own preference. The developed SPEA reproduced the same results of an existing GAs-based multi objective technique in the literature. The proposed approach has been developed and implemented on multiple projects of different sizes. The results proved the effectiveness of the SPEA to solve finance-based scheduling problems of multiple projects considering the conflict in their profit realization.

Research highlights
► We used SPEA to devise Pareto-optimal finance-based schedules of multiple projects.
► The multiple projects profit maximization is a multiobjective optimization problem.
► The profit values of the projects constitute a set of conflicting objectives.
► We validated the developed SPEA by reproducing the results reported in the literature.