An optimization algorithm inspired by musical composition in constrained optimization problems
Román Anselmo Mora-Gutiérrez, Eric Alfredo Rincón-García, Javier Ramírez-Rodríguez, Antonin Ponsich, Oscar Herrera-Alcántara, Pedro Lara-Velázquez · Revista de Matemática Teoría y Aplicaciones · 2013
Many real-world problems can be expressed as an instance of the constrained nonlinear optimization problem (CNOP). This problem has a set of constraints specifies the feasible solution space. In the last years several algorithms have been proposed and developed for tackling CNOP. In this paper, we present a cultural algorithm for constrained optimization, which is an adaptation of “Musical Composition Method” or MCM, which was proposed in [33] by Mora et al. We evaluated and analyzed the performance of MCM on five test cases benchmark of the CNOP. Numerical results were compared to evolutionary algorithm based on homomorphous mapping [23], Artificial Immune System [9] and anti-culture population algorithm [39]. The experimental results demonstrate that MCM significantly improves the global performances of the other tested metaheuristics on same of benchmark functions.