Now showing items 1-10 of 16
Benchmark Functions for the CEC'2018 Competition on Dynamic Multiobjective Optimization
(Newcastle University, 2018-01)
Convergence versus diversity in multiobjective optimization
Convergence and diversity are two main goals in multiobjective optimization. In literature, most existing multiobjective optimization evolutionary algorithms (MOEAs) adopt a convergence-first-and-diversity-second environmental ...
A steady-state and generational evolutionary algorithm for dynamic multi-objective optimization
(IEEE Press, 2016-05-10)
This paper presents a new algorithm, called steady-state and generational evolutionary algorithm, which combines the fast and steadily tracking ability of steady-state algorithms and good diversity preservation of generational ...
A Fast Strength Pareto Evolutionary Algorithm Incorporating Predefined Preference Information
(IEEE Press, 2015-09)
Strength Pareto Evolutionary Algorithm 2 (SPEA2) has achieved great success for handling multiobjective optimization problems. However, it has been widely reported that SPEA2 gets subjected to a huge amount of computational ...
Less detectable environmental changes in dynamic multiobjective optimisation
(ACM Press, 2018-05-04)
Multiobjective optimisation in dynamic environments is challenging due to the presence of dynamics in the problems in question. Whilst much progress has been made in benchmarks and algorithm design for dynamic multiobjective ...
A scalable test suite for dynamic multiobjective optimization
Dynamic multiobjective optimization (DMO) has gained increasing attention in recent years. Test problems are of great importance in order to facilitate the development of advanced algorithms that can handle dynamic ...
Evolutionary Dynamic Multiobjective Optimization: Benchmarks and Algorithm Comparisons
Dynamic multi-objective optimization has received growing research interest in recent years since many real-world optimization problems appear to not only have multiple objectives that conflict with each other but also ...
Scalarizing functions in decomposition-based multiobjective evolutionary algorithms
(IEEE Press, 2017)
Decomposition-based multiobjective evolutionary algorithms have received increasing research interests due to their high performance for solving multiobjective optimization problems. However, scalarizing functions, which ...
An adaptive penalty-based boundary intersection approach for multiobjective evolutionary algorithm based on decomposition
(IEEE Press, 2016-07)
The multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem into a number of sing-objective subproblems and solves them collaboratively. Since its introduction, ...
A strength pareto evolutionary algorithm based on reference direction for multi-objective and many-objective optimization
(IEEE Press, 2017-03-24)
While Pareto-based multi-objective optimization algorithms continue to show effectiveness for a wide range of practical problems that involve mostly two or three objectives, their limited application for many-objective ...