This paper aims to achieve the exact resolution of an optimal power flow (OPF) problem in an electrical network. In the OPF, the goal is to plan the production and distribution of electrical power flows to cover, at minimal fuel cost, the consumption at various points in the network. Three variants of the OPF problem are studied in this manuscript. The first one, OPF corresponds to the case where power production costs in the network are modeled with a quadratic cost. In the second variant, OPF with outages of some lines, we clarify the extent to which power flow is affected by the outages and the increasing number of overloaded lines. Finally, the last variant, secured OPF corresponds to the case where the management of production units can respect the power limit of each line by rescheduling power production units. The study focuses on congestion management in the IEEE 30 bus system by applying a model for OPF, incorporating data from both transmission lines and generators. The research proposes a Hunting Optimization Technique which is named “Multi-Objective Ant Lion Optimizer (MOALO)” to solve single and multi-objective optimization problems to find a solution for management pricing, comparing results with other research methods to show the effectiveness of the applied approach and the mathematical model representing congestion management.