The triple constraints (cost, time, and quality) are the major axis on which success criteria for projects are built. Therefore, successful initiatives result from using resources as efficiently as possible to meet these objectives. On the other hand, institutional construction projects demand careful consideration to succeed without a lot of variation orders. One such factor is allocating resources and planning the project effectively. The issue of distributing resources among institutional construction sites as efficiently as possible is addressed when construction companies handle a variety of simultaneous tasks, each of which has a separate exchange rate. Optimizing specified resources performance indices (V_(m,) RR and RIC) is just one of many optimality factors. The goal of this research is to use a leveling technique by a proposed genetic algorithm to minimize the maximum value of the used resource V_m, maximize the rate of resource usage RR, and minimize the resource improvement coefficient RIC to get as close to 1. Since all of the indices reflect resource fluctuation, during the implementation phase, this reflection also determines the activity schedule. This led to a result for resource leveling (optimal indices) and resource allocation following the optimizing procedure (new schedule). In this study, various fictitious scenarios of multi-resource activities for a hypothetical project with three different resources are initially taken into consideration to evaluate the suggested algorithm and determine its suitability. Additionally, an actual case study with all potential outcomes of a multi-resource project (materials, manpower, and machine) will be presented to validate the suggested approach. Ultimately, decide which implementation scenario is the best.