Chaotic Search Based Equilibrium Optimizer for Dealing with Nonlinear Programming and Petrochemical Application

In this article, chaotic search based constrained equilibrium optimizer algorithm (CS-CEOA) is suggested by integrating a novel heuristic approach called with chaos theory-based local for solving general non-linear programming. CS-CEOA consists of two phases, the first one (phase I) aims to detect an approximate solution, avoiding being stuck in minima. phase II, chaos-based improves performance obtain best optimal solution. For every infeasible repair function implemented way such that, new feasible solution created on line segment defined reference point and itself. Due fast globally converging evolutionary algorithms search’s exhaustive search, could locate true applying limited area from Phase I. The efficiency studied over multi-suites benchmark problems including constrained, unconstrained, CEC’05 problems, application blending four ingredients, three feed streams, tank, products create some certain specific chemical properties, also satisfy target costs. results were compared standard as PSO GA, many hybrid same simulation environment approve its superiority detecting selected counterparts.