Multi-objective Cultural Algorithms

Multi-objective optimization is a widely applicable technique in Engineering and Computer Science. In the past, Cultural Algorithms have been used to solve complex optimization and design problems with success. In this paper, we extend the Cultural Algorithm Framework to handle multi-objective problems. The resultant system, Multi-Objective Cultural Algorithms (MOCA), can be used independently or as a supplement to other MO optimization methods. We compare the performance of our algorithm with NSGA-II using problems from the DTLZ test suite, a popular MOEA test suite and found that Cultural Algorithms are a promising technique for solving multi-objective problems.