Digital Commons Network^™

Dominance In Multi-Population Cultural Algorithms, Santosh Upadhyayula

Electronic Theses and Dissertations

We propose a new approach that can be used for solving the knowledge migration issue in multi-population cultural algorithms (MPCA). In this study we introduce a new method to enable the migration of individuals from one population to another using the concept of complete dominance applied to MPCA. The MPCA’s artificial population comprises of agents that belong to a certain sub-population. In this work we create a dominance multi population cultural algorithm (D-MPCA) with a network of populations that implements a dominance strategy. We hypothesize that the evolutionary advantage of dominance can help improve the performance of MPCA in general …

Heuristics For Multi-Population Cultural Algorithm, Xinyu He

Electronic Theses and Dissertations

Cultural Algorithm (CA) is one of the Evolutionary Algorithms (EAs) which de- rives from the cultural evolution process in nature. As an extended version of the CA, the Multi-population Cultural Algorithm (MPCA) has multiple population spaces. Since the evolutionary information can be exchanged among the sub-populations, the MPCA can obtain better results than the CA in optimization problems. In this thesis, we introduce heuristics to improve the MPCA. The heuristic strate- gies target the existing weaknesses in MPCAs. Four strategies are developed address- ing these weaknesses, including the individual memory heuristic, the social interaction heuristic, the dynamic knowledge migration interval …

The Impact Of Increased Optimization Problem Dimensionality On Cultural Algorithm Performance, Yang Yang

Wayne State University Theses

ABSTRACT

The Impact of Increased Optimization Problem Dimensionality on

Cultural Algorithm Performance

by

Yang Yang

August 2015

Advisor: Dr. Robert Reynolds

Major: Computer Science

Degree: Master of Science

In this thesis, we investigate the performance of Cultural Algorithms when dealing with the increasing dimensionality of optimization problems. The research is based on previous cultural algorithm approaches with the Cultural Algorithms Toolkit, CAT 2.0, which supports a variety of co-evolutionary features at both the knowledge and population levels. In this project, the system was applied to the solution of 60 randomly generated problems that ranged from 2-dimensional to 5-dimensional problem spaces. …