Decomposition-based chemical reaction optimization (CRO) and an extended CRO algorithms for multiobjective optimization

Multiobjective optimization is an essential and challenging topic in the domains of science and engineering optimization. An effective decomposition-based chemical reaction optimization metaheuristic algorithm (MOCRO/D) for solving multiobjective optimization problems (MOPs) is proposed in this paper. In the proposed algorithm, each decomposed sub-problem is represented by a chemical molecule. All molecules are divided into a few groups and each molecule has several neighboring molecules. During the search, each molecule records its potential energy (optimal solution), the hits of number and the kinetic energy. MOCRO/D has four operators, i.e., on-wall ineffective collision, inter-molecular ineffective collision, decomposition, and synthesis. To explore the search space efficiently, polynomial mutation and multiple molecule collision operators are introduced in the inter-molecular collision and synthesis operator. The inter-molecular ineffective collision operator uses three molecules to collide, which can improve the information interacting with each other with a certain probability. The extended synthesis operator could increase the global search ability. Extended operators for MOCRO/D (MOECRO/D) are proposed that can better optimize the variables related problems. The proposed approach is compared with other metaheuristic algorithms available in the specialized literature. Results indicate that the proposed approach is competitive in most of the test instances.