Multi-resource allocation and leveling in multi-project (MR-AL-MP) scheduling refers to the attempt of producing a project schedule with minimum project duration and maximum resource utilization while complying with all precedence and resource availability constraints in a multi-project environment that involves multiple types of resources. This study proposes an optimization model that integrates both resource allocation and leveling models into a unified framework. The model employs the release and rehire (RRH) or resource idle days (RID) and resource intensity (RI) as the resource leveling metrics. The present study develops a modified version of the well-known NSGA-II, called Hybrid-Chromosome NSGA-II, as the optimization algorithm. To validate the performance of the proposed model and algorithm, they are applied to two case studies. The performance is compared with two benchmark metaheuristic algorithms: Multi-Objective Particle Swam Optimization (MOPSO) and Multi-Objective Symbiotic Organisms Search (MOSOS). From the results obtained, it is shown that the proposed model and algorithm are able to produce a set of non-dominated solutions to study the feasible trade-off relationships between the objectives: project duration, RRH or RID, and RI. Furthermore, the Hybrid-Chromosome NSGA-II is superior to MOPSO and MOSOS in terms of the quality, spread, and diversity of the solutions.

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