Finance-based scheduling of multiple projects: Comparative study of multi-objective optimization techniques

Managing multiple construction projects involves the allocation of limited funds among multiple ongoing projects, which increases the complexity of the scheduling process. As a matter of fact, the cash deficit problem is considered as being a major threat to contractor’s financial stability. Unless project scheduling and financing are carefully integrated, it becomes inevitable that contractors discard schedules during the construction phase which results in extra overhead costs and liquidated damages. Thus, the development of a model that integrates the two management functions of scheduling and financing becomes essential to establish executable schedules that simultaneously optimizes multiple project objectives. This research proposes the development of a finance-based scheduling multi-objective optimization model for multiple projects using the elitist non-dominated sorting genetic algorithm (NSGA-II). The model involves the minimization of three conflicting objectives, namely: duration of multiple projects, financing costs, and the maximum required credit. Further, the obtained model’s results using the NSGA-II technique will be compared with a previously developed similar model developed earlier in the literature using the multi-objective technique of Strength Pareto Evolutionary Algorithm (SPEA).