Chemical Reaction Optimization

Article MQL5 articles

Summary

This article introduces chemical reaction optimization (CRO), a population-based metaheuristic inspired by molecular reactions and energy conservation. Candidate solutions are treated as molecules, with objective-function values represented through potential energy and additional kinetic energy used to permit transitions. The method balances exploration and local refinement through four operators: ineffective collisions that perturb one or two candidates, decomposition that splits a candidate into two, and synthesis that combines two candidates into one. The article gives procedural descriptions of these operations and discusses a Gaussian perturbation step for changing solution coordinates.

The document is a first installment focused on concepts and operator implementation, not a completed empirical evaluation. It explicitly notes that the presented formulation leaves important questions about mapping numerical energy to fitness and how that choice affects search behavior. It provides no benchmark results or trading application in this part; experiments on test functions are deferred to a later article. CRO is therefore presented as a flexible optimization framework, but its effectiveness for a particular objective, including trading parameter selection, would need to be measured independently.

Key ideas

CRO represents candidate solutions as molecules with potential and kinetic energy.
Four reaction operators perturb, split, or combine candidate solutions to support exploration and refinement.
Energy accounting governs whether proposed molecular changes are accepted and how residual energy is assigned.
Coordinate perturbations can be bounded by the search range and sampled with a Gaussian distribution.
The article flags unresolved choices in relating energy values to objective fitness and provides no benchmark results in this installment.

Chemical Reaction Optimization: Operators for Population-Based Search

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