Stochastic Ranking Algorithm for Many-Objective Optimization Based on Multiple Indicators

نویسندگان
چکیده

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

Effective ranking + speciation = Many-objective optimization

Multiobjective optimization problems have been widely addressed using evolutionary computation techniques. However, when dealing with more than three conflicting objectives (the so-called many-objective problems), the performance of such approaches deteriorates. The problem lies in the inability of Pareto dominance to provide an effective discrimination. Alternative ranking methods have been su...

متن کامل

Evolutionary Many-Objective Optimization Based on Kuhn-Munkres' Algorithm

In this paper, we propose a new multi-objective evolutionary algorithm (MOEA), which transforms a multi-objective optimization problem into a linear assignment problem using a set of weight vectors uniformly scattered. Our approach adopts uniform design to obtain the set of weights and Kuhn-Munkres’ (Hungarian) algorithm to solve the assignment problem. Differential evolution is used as our sea...

متن کامل

GPGPU-Compatible Archive Based Stochastic Ranking Evolutionary Algorithm (G-ASREA) for Multi-Objective Optimization

In this paper, a GPGPU (general purpose graphics processing unit) compatible Archived based Stochastic Ranking Evolutionary Algorithm (G-ASREA) is proposed, that ranks the population with respect to an archive of non-dominated solutions. It reduces the complexity of the deterministic ranking operator from O(mn) to O(man) and further speeds up ranking on GPU. Experiments compare G-ASREA with a C...

متن کامل

Adaptive -Ranking and Distribution Search on Evolutionary Many-objective Optimization

In this work, we study the effectiveness of Adaptive -Ranking for distribution search in the context of many-objective optimization. Adaptive -Ranking re-classifies sets of non-dominated solutions using iteratively a randomized sampling procedure that applies -dominance with a mapping function f(x) 7→ f (x) to bias selection towards the distribution of solutions implicit in the mapping. We anal...

متن کامل

Weight-based Fish School Search algorithm for Many-Objective Optimization

Optimization problems with more than one objective consist in a very attractive topic for researchers due to its applicability in real-world situations. Over the years, the research effort in the Computational Intelligence field resulted in algorithms able to achieve good results by solving problems with more than one conflicting objective. However, these techniques do not exhibit the same perf...

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: IEEE Transactions on Evolutionary Computation

سال: 2016

ISSN: 1089-778X,1089-778X,1941-0026

DOI: 10.1109/tevc.2016.2549267