A Testbed for Solving Optimization Problems Using Cultural Algorithms
نویسندگان
چکیده
This paper introduce a cultural algorithm based testbed which allows one to plug and play various combinations of evolution components for solving constrained numerical optimization. Our cultural algorithm framework combines weak search method with knowledge representation scheme for collecting and reasoning knowledge about individual experience. Currently genetic algorithm based software package GENOCOP(GEnetic algorithm for Numerical Optimization for COnstrained Problems) and rudimentary EP(Evolutionary Programming) are embedded in the cultural algorithm framework. Preliminary results suggest that the belief space is an important contributor to the problem solving process for both systems when the number of constraints on the problem become large enough.
منابع مشابه
Adaptive Rule-Base Influence Function Mechanism for Cultural Algorithm
This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...
متن کاملSolving Data Clustering Problems using Chaos Embedded Cat Swarm Optimization
In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...
متن کاملSolving Data Clustering Problems using Chaos Embedded Cat Swarm Optimization
In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...
متن کاملFOA: ‘Following’ Optimization Algorithm for solving Power engineering optimization problems
These days randomized-based population optimization algorithms are in wide use in different branches of science such as bioinformatics, chemical physics andpower engineering. An important group of these algorithms is inspired by physical processes or entities’ behavior. A new approach of applying optimization-based social relationships among the members of a community is investigated in this pa...
متن کاملSolving Fractional Programming Problems based on Swarm Intelligence
This paper presents a new approach to solve Fractional Programming Problems (FPPs) based on two different Swarm Intelligence (SI) algorithms. The two algorithms are: Particle Swarm Optimization, and Firefly Algorithm. The two algorithms are tested using several FPP benchmark examples and two selected industrial applications. The test aims to prove the capability of the SI algorithms to s...
متن کامل