Author Archives: Community

IEEE Transactions on Evolutionary Computation information for authors

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. Continue reading

Comments Off on IEEE Transactions on Evolutionary Computation information for authors

Quantifying Variable Interactions in Continuous Optimization Problems

Interactions between decision variables typically make an optimization problem challenging for an evolutionary algorithm (EA) to solve. Exploratory landscape analysis (ELA) techniques can be used to quantify the level of variable interactions in an opt… Continue reading

Comments Off on Quantifying Variable Interactions in Continuous Optimization Problems

IEEE World Congress on Computational Intelligence

Describes the above-named upcoming special issue or section. May include topics to be covered or calls for papers. Continue reading

Comments Off on IEEE World Congress on Computational Intelligence

A Multiobjective Cooperative Coevolutionary Algorithm for Hyperspectral Sparse Unmixing

Sparse unmixing of hyperspectral data is an important technique aiming at estimating the fractional abundances of the endmembers. Traditional sparse unmixing is faced with the $boldsymbol {l_{0}}$ -norm problem which is an NP-hard problem. Sparse unmi… Continue reading

Comments Off on A Multiobjective Cooperative Coevolutionary Algorithm for Hyperspectral Sparse Unmixing

A Classification and Comparison of Credit Assignment Strategies in Multiobjective Adaptive Operator Selection

Adaptive operator selection (AOS) is a high-level controller for an optimization algorithm that monitors the performance of a set of operators with a credit assignment strategy and adaptively applies the high performing operators with an operator selection strategy. AOS can improve the overall performance of an optimization algorithm across a wide range of problems, and it has shown promise on single-objective problems where defining an appropriate credit assignment that assesses an operator’s impact is relatively straightforward. However, there is currently a lack of AOS for multiobjective problems (MOPs) because defining an appropriate credit assignment is nontrivial for MOPs. To identify and examine the main factors in effective credit assignment strategies, this paper proposes a classification that groups credit assignment strategies by the sets of solutions used to assess an operator’s impact and by the fitness function used to compare those sets of solutions. Nine credit assignment strategies, which include five newly proposed ones, are compared experimentally on standard benchmarking problems. Results show that eight of the nine credit assignment strategies are effective in elevating the generality of a multiobjective evolutionary algorithm and outperforming a random operator selector. Continue reading

Comments Off on A Classification and Comparison of Credit Assignment Strategies in Multiobjective Adaptive Operator Selection

Many-Objective Evolutionary Algorithms Based on Coordinated Selection Strategy

Selection strategy, including mating selection and environmental selection, is a key ingredient in the design of evolutionary multiobjective optimization algorithms. Existing approaches, which have shown competitive performance in low-dimensional multi… Continue reading

Comments Off on Many-Objective Evolutionary Algorithms Based on Coordinated Selection Strategy

A Novel Image Representation Framework Based on Gaussian Model and Evolutionary Optimization

We propose a novel image representation framework based on Gaussian model and evolutionary optimization (EO). In this framework, image patches are categorized into smooth and nonsmooth ones, and the two categories are treated distinctively. For a smoot… Continue reading

Comments Off on A Novel Image Representation Framework Based on Gaussian Model and Evolutionary Optimization

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization

Particle swarm optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to… Continue reading

Comments Off on Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization

IEEE Transactions on Evolutionary Computation Society Information

Provides a listing of the editorial board, current staff, committee members and society officers. Continue reading

Comments Off on IEEE Transactions on Evolutionary Computation Society Information

Adaptive Multimodal Continuous Ant Colony Optimization

Seeking multiple optima simultaneously, which multimodal optimization aims at, has attracted increasing attention but remains challenging. Taking advantage of ant colony optimization (ACO) algorithms in preserving high diversity, this paper intends to … Continue reading

Comments Off on Adaptive Multimodal Continuous Ant Colony Optimization