  Optimization techniques are frequently applied in science and engineering
research and development. Evolutionary algorithms, as a kind of general-purpose
metaheuristic, have been shown to be very effective in solving a wide range of
optimization problems. A recently proposed chemical-reaction-inspired
metaheuristic, Chemical Reaction Optimization (CRO), has been applied to solve
many global optimization problems. However, the functionality of the
inter-molecular ineffective collision operator in the canonical CRO design
overlaps that of the on-wall ineffective collision operator, which can
potential impair the overall performance. In this paper we propose a new
inter-molecular ineffective collision operator for CRO for global optimization.
To fully utilize our newly proposed operator, we also design a scheme to adapt
the algorithm to optimization problems with different search space
characteristics. We analyze the performance of our proposed algorithm with a
number of widely used benchmark functions. The simulation results indicate that
the new algorithm has superior performance over the canonical CRO.
