<![CDATA[Operations research methods, specifically linear programming with an integer approach, can be applied to assist the scheduling and resource allocation process in production environments. In many cases, companies face limitations in time, labor, and machine capacity, requiring calculation methods capable of providing the most efficient decisions. Through mathematical modeling based on integer linear programming, this study develops a solution that can determine optimal work schedules while allocating resources appropriately within existing constraints. The analysis shows that this method can reduce wasted time, improve capacity utilization, and facilitate more measured and systematic decision-making. Resource scheduling and distribution are crucial components in many sectors, including manufacturing, transportation, education, and information systems. In practice, decision-making is often complicated by certain constraints, such as limited labor, machines, or indivisible work hours. To address these situations, Integer Linear Programming (ILP) is a frequently used method, particularly for optimization problems involving discrete variables. Through this literature review, researchers analyze various studies that use ILP in the context of scheduling and resource distribution. The discussion covers modeling methods, solution methods such as branch and bound and cutting plane, and applications to various real-world case studies. The research demonstrates that ILP is capable of providing optimal or near-optimal solutions, even when faced with complex constraints.]]>
