Diversity Based on Entropy: A Novel Evaluation Criterion in Multi-objective Optimization Algorithm
نویسندگان
چکیده
منابع مشابه
Diversity Based on Entropy: A Novel Evaluation Criterion in Multi-objective Optimization Algorithm
Quality assessment of Multi-objective Optimization algorithms has been a major concern in the scientific field during the last decades. The entropy metric is introduced and highlighted in computing the diversity of Multi-objective Optimization Algorithms. In this paper, the definition of the entropy metric and the approach of diversity measurement based on entropy are presented. This measuremen...
متن کاملMOEICA: Enhanced multi-objective optimization based on imperialist competitive algorithm
In this paper, a multi-objective enhanced imperialist competitive algorithm (MOEICA) is presented. The main structures of the original ICA are employed while some novel approaches are also developed. Other than the non-dominated sorting and crowding distance methods which are used as the main tools for comparing and ranking solutions, an auxiliary comparison approach called fuzzy possession is ...
متن کاملEntropy-based multi-objective genetic algorithm for design optimization
Obtaining a fullest possible representation of solutions to a multiobjective optimization problem has been a major concern in Multi-Objective Genetic Algorithms (MOGAs). This is because a MOGA, due to its very nature, can only produce a discrete representation of Pareto solutions to a multiobjective optimization problem that usually tend to group into clusters. This paper presents a new MOGA, o...
متن کاملEntropy Diversity in Multi-Objective Particle Swarm Optimization
Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly ...
متن کاملOptimization of Agricultural BMPs Using a Parallel Computing Based Multi-Objective Optimization Algorithm
Beneficial Management Practices (BMPs) are important measures for reducing agricultural non-point source (NPS) pollution. However, selection of BMPs for placement in a watershed requires optimizing available resources to maximize possible water quality benefits. Due to its iterative nature, the optimization typically takes a long time to achieve the BMP trade-off results which is not desirable ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Intelligent Systems and Applications
سال: 2012
ISSN: 2074-904X,2074-9058
DOI: 10.5815/ijisa.2012.10.12