Semantics in Multi-objective Genetic Programming

نویسندگان

چکیده

Semantics has become a key topic of research in Genetic Programming (GP). refers to the outputs (behaviour) GP individual when this is run on dataset. The majority works that focus semantic diversity single-objective indicates it highly beneficial evolutionary search. Surprisingly, there minuscule conducted semantics Multi-objective (MOGP). In work we make leap beyond our understanding MOGP and propose SDO: Semantic-based Distance as an additional criteriOn. This naturally encourages MOGP. To do so, find pivot less dense region first Pareto front (most promising front). then used compute distance between every population. resulting criterion be optimised favour diversity. We also use two other semantic-based methods baselines, called Semantic Similarity-based Crossover Crowding Distance. Furthermore, Non-dominated Sorting Algorithm II Strength Evolutionary 2 for comparison too. unbalanced binary classification problems consistently show how proposed SDO approach produces more non-dominated solutions better diversity, leading statistically significant results, using hypervolume results evaluation measure, compared rest four methods.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On the Use of Semantics in Multi-objective Genetic Programming

Research on semantics in Genetic Programming (GP) has increased dramatically over the last number of years. Results in this area clearly indicate that its use in GP can considerably increase GP performance. Motivated by these results, this paper investigates for the first time the use of Semantics in Muti-Objective GP within the well-known NSGA-II algorithm. To this end, we propose two forms of...

متن کامل

Using Genetic Algorithm in Solving Stochastic Programming for Multi-Objective Portfolio Selection in Tehran Stock Exchange

Investor decision making has always been affected by two factors: risk and returns. Considering risk, the investor expects an acceptable return on the investment decision horizon. Accordingly, defining goals and constraints for each investor can have unique prioritization. This paper develops several approaches to multi criteria portfolio optimization. The maximization of stock returns, the pow...

متن کامل

Multi-objective Genetic Programming for Visual Analytics

Visual analytics is a human-machine collaboration to data modeling where extraction of the most informative features plays an important role. Although feature extraction is a multi-objective task, the traditional algorithms either only consider one objective or aggregate the objectives into one scalar criterion to optimize. In this paper, we propose a Pareto-based multi-objective approach to fe...

متن کامل

Multi-Objective Stochastic Programming in Microgrids Considering Environmental Emissions

This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity market prices, unpredictable load demand, and uncertain wind and solar power values, du...

متن کامل

ذخیره 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: Applied Soft Computing

سال: 2022

ISSN: ['1568-4946', '1872-9681']

DOI: https://doi.org/10.1016/j.asoc.2021.108143