A Self-Adaptive Hybrid Optimization Algorithm for Solving Consecutive Reaction Problem

The actual temperature control for consecutive reaction problem is a complex optimization problem. Genetic algorithms (GA) is a metaheuristic inspired by imitating the processes observed during natural evolution. It has a strong global search ability and less computation time, but it exists the premature convergence and poor stability. Ant colony optimization (ACO) is a metaheuristic inspired by imitating the behavior of real ants. It has the robustness and parallel computation, but it exists the slow convergence speed and stagnation phenomenon. In this paper, a new genetic and ant colony self-adaptive hybrid (NGASAH) algorithm based on the chaotic searching strategy, multi-populations and self-adaptive parameter control strategies is presented. In the proposed NGASAH algorithm, the chaotic searching strategy is used to avoid the optimal solution. The strategy of the multiple populations is used to avoid to converge to a local extreme point of all particles. The strategy of self-adaptive parameter control...