A Robust Bi-objective Optimization Model for Resource Levelling Project Scheduling Problem with Discounted Cash Flows

Due to limited financial resources and high costs of infrastructure projects, project stakeholders seek gain maximum profits with optimal resource utilization as well cost time minimization. Therefore, this study presents a multi-mode resource-constrained scheduling model considering the uncertain parameters together goals maximizing net present value minimizing usage fluctuation. Also, assumptions related real-world projects regarding activities, limitation renewable resources, deadline are incorporated into proposed model. Moreover, robust method is presented better deal inherent uncertainties time. The solved exact named lexicographic goal programming (LGP). NP-hardness problem, two metaheuristic algorithms Non-dominated Sorting Genetic Algorithm (NSGA-II) Multi-Objective Particle Swarm Optimization (MOPSO) applied solve various medium large size problems. obtained results indicate efficiency in solving problem performance MOPSO algorithm compared NSGA-II terms five indices. Furthermore, implemented an offshore equipment installation phase wellhead platform project. Finally, sensitivity analysis performed different conservation levels, evaluated by Monte Carlo simulation three normal, uniform triangular distributions. findings demonstrate that robustness against variations parameters.