Dynamic Objective Sampling in Many-objective Optimization
نویسندگان
چکیده
منابع مشابه
Using Different Many-Objective Techniques in Particle Swarm Optimization for Many Objective Problems: An Empirical Study
Pareto based Multi-Objective Evolutionary Algorithms face several problems when dealing with a large number of objectives. In this situation, almost all solutions become nondominated and there is no pressure towards the Pareto Front. The use of Particle Swarm Optimization algorithm (PSO) in multi-objective problems grew in recent years. The PSO has been found very efficient in solve Multi-Objec...
متن کاملEffective 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 کاملMany objective optimization and hypervolume based search
Multiobjective optimization problems occur frequently in practice where multiple objectives have to be optimized simultaneously and the goal is to find or approximate the set of Pareto-optimal solutions. Multiobjective evolutionary algorithms (MOEAs) are one type of randomized search heuristics that are well-suited for multiobjective optimization problems due to their ability of computing a set...
متن کاملMany-Objective Optimization: An Engineering Design Perspective
Evolutionary multicriteria optimization has traditionally concentrated on problems comprising 2 or 3 objectives. While engineering design problems can often be conveniently formulated as multiobjective optimization problems, these often comprise a relatively large number of objectives. Such problems pose new challenges for algorithm design, visualisation and implementation. Each of these three ...
متن کاملMany Objective Optimisation: Direct Objective Boundary Identification
This paper describes and demonstrates a new and highly innovative technique that identifies an approximation of the entire bounding surface of the feasible objective region directly, including deep concavities, disconnected regions and the edges of interior holes in the feasible areas. The Pareto front is a subset of the surface of the objective boundary and can be extracted easily. Importantly...
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: Procedia Computer Science
سال: 2015
ISSN: 1877-0509
DOI: 10.1016/j.procs.2015.08.117