A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization
نویسندگان
چکیده
منابع مشابه
IGD Indicator-based Evolutionary Algorithm for Many-objective Optimization Problems
Inverted Generational Distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of multiand manyobjective evolutionary algorithms. In this paper, an IGD indicatorbased evolutionary algorithm for solving many-objective optimization problems (MaOPs) has been proposed. Specifically, the IGD indicator is employed in each gen...
متن کاملA new uniform evolutionary algorithm based on decomposition and CDAS for many-objective optimization
The convergence and the diversity are two main goals of an evolutionary algorithm for many-objective optimization problems. However, achieving these two goals simultaneously is the difficult and challenging work for multi-objective evolutionary algorithms. A uniform evolutionary algorithm based on decomposition and the control of dominance area of solutions (CDAS) is proposed to achieve these t...
متن کاملEvolutionary 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 کاملA Predictive Pareto Dominance Based Algorithm for Many-Objective Problems
1. Abstract Multiobjective genetic algorithms (MOGAs) have successfully been used on a wide range of real world problems. However, it is generally accepted that the performance of most state-of-the-art multiobjective genetic algorithms tend to perform poorly for problems with more than four objectives, termed many-objective problems. The contribution of this paper is a new approach for identify...
متن کاملA New Evolutionary Decision Theory for Many-Objective Optimization Problems
In this paper the authors point out that the Pareto Optimality is unfair, unreasonable and imperfect for Many-objective Optimization Problems (MOPs) underlying the hypothesis that all objectives have equal importance. The key contribution of this paper is the discovery of the new definition of optimality called ε-optimality for MOP that is based on a new conception, so called ε-dominance, which...
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: IEEE Transactions on Evolutionary Computation
سال: 2016
ISSN: 1089-778X,1089-778X,1941-0026
DOI: 10.1109/tevc.2015.2420112