Cultural algorithms (CAs) are one of the metaheuristics which can be adapted in order to work in multiobjective optimization environments. On the other hand, portfolio selection problem (PSP) is a wellknow problem in literature. However, only a few articles have applied evolutionary multi-objective (EMO) algorithms to these problems and articles presenting CAs applied to the PSP have not been f...

This paper presents a new hybrid Cultural Algorithm (CA) based particle swarm optimization (PSO) that converges to a significantly more accurate solution then existing particle swarm optimization and which has also been applied to the linear brushless DC motor PID controller design. The utility of hybrid CA based PSO is demonstrated by determining the optimal proportional-integral-derivative (P...

We test for universal patterns in cultural evolution by Guttman scaling on two different worldwide samples of archaeological traditions and on well-known archaeological sequences. The evidence is generally consistent with universal evolutionary sequences. We also present evidence for some punctuated evolutionary events. [

This study is a 6-month follow-up of a randomized pilot evaluation of standard one-session treatment (OST-S) versus culturally adapted OST (OST-CA) with phobic Asian Americans. OST-CA included seven cultural adaptations drawn from prior research with East Asians and Asian Americans. Results from 1-week and 6-month follow-up show that both OST-S and OST-CA were effective at reducing phobic sympt...

palaeoclimatology is a basic approach for the neolithic archaeology. the world-wide climate changes during the holocene ca. 10th millennia bc was an introduction to the neolithic revolution and the emergence of early villages. early holocene climate oscillations changed the biogeography of iran. consequently, its temperature, fauna and flora had been changed during ca. 12800- 3500 bc; and final...

This paper proposes a new method based on the cultural algorithm to solve graph coloring problem (GCP). Graph coloring problem involves finding the minimum number of colors for coloring the graph vertices such that adjacent vertices have distinct colors. In this paper various components of cultural algorithm have been implemented to solve GCP with a self adaptive behavior in an efficient manner...

This paper proposes a new method based on the cultural algorithm to solve graph coloring problem (GCP). Graph coloring problem involves finding the minimum number of colors for coloring the graph vertices such that adjacent vertices have distinct colors. In this paper various components of cultural algorithm have been implemented to solve GCP with a self adaptive behavior in an efficient manner...

The key idea behind Cultural Algorithms is to explcitly acquire problem-solving knowledge (beliefs) from the evolving population in the form of schemata and in return apply that knowledge to guide the search [Reynolds 1993, 1996]. In solving nonlinear constraint optimization problems, the key problem is how to represent and store the knowledge about the constraints. Previously, Chung [1996, 199...

Electronic circuit optimization design is important research field in engineering applications. Circuit scale and the time of evaluate the circuit are the challenge problems for circuit optimization design algorithm and the traditional optimization algorithms cannot solve the two problems very well. Cultural Algorithms are a class of computational models derived from observing the cultural evol...

In this paper a computational model of the cultural evolution process is described. This model integrates several traditional approaches to modeling cultural evolution into a common conceptual framework. This framework depicts cultural evolution as a process of dual inheritance. At the micro-evolutionary level there is a population of individuals, each described in terms of a set of behavioral ...