Multiobjective evolutionary algorithms: A survey of the state of the art
A multiobjective optimization problem involves several conflicting objectives and has a set of
Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary …
Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary …
Review of multiple unmanned surface vessels collaborative search and hunting based on swarm intelligence
G Wu, T Xu, Y Sun, J Zhang - International Journal of …, 2022 - journals.sagepub.com
In recent years, the research of multiple unmanned surface vessels collaboration has
received great attention. More and more researchers have proposed different methods of …
received great attention. More and more researchers have proposed different methods of …
A guided population archive whale optimization algorithm for solving multiobjective optimization problems
This paper proposes a new multiobjective algorithm by extending the recently Whale
Optimization Algorithm (WOA) to solve multiobjective optimization problems. Our algorithm …
Optimization Algorithm (WOA) to solve multiobjective optimization problems. Our algorithm …
A new local search-based multiobjective optimization algorithm
In this paper, a new multiobjective optimization framework based on nondominated sorting
and local search (NSLS) is introduced. The NSLS is based on iterations. At each iteration …
and local search (NSLS) is introduced. The NSLS is based on iterations. At each iteration …
Multiple objective ant colony optimisation
Abstract Multiple Objective Optimisation is a fast growing area of research, and
consequently several Ant Colony Optimisation approaches have been proposed for a variety …
consequently several Ant Colony Optimisation approaches have been proposed for a variety …
An ant colony optimization algorithm with evolutionary experience-guided pheromone updating strategies for multi-objective optimization
H Zhao, C Zhang - Expert Systems with Applications, 2022 - Elsevier
Since the multi-objective ant colony optimization algorithm consumes a massive cost of time
and computation resources, improving its convergence performance is essential. This paper …
and computation resources, improving its convergence performance is essential. This paper …
Performance analysis of the multi-objective ant colony optimization algorithms for the traveling salesman problem
I Ariyasingha, TGI Fernando - Swarm and Evolutionary Computation, 2015 - Elsevier
Most real world combinatorial optimization problems are difficult to solve with multiple
objectives which have to be optimized simultaneously. Over the last few years, researches …
objectives which have to be optimized simultaneously. Over the last few years, researches …
A decomposition-based many-objective ant colony optimization algorithm with adaptive solution construction and selection approaches
H Zhao, C Zhang, X Zheng, C Zhang… - Swarm and Evolutionary …, 2022 - Elsevier
The ant colony optimization algorithm (ACO) had an exceptional performance in solving
discrete optimization problems because of its design in solution construction and search …
discrete optimization problems because of its design in solution construction and search …
Comparative study of ant colony algorithms for multi-objective optimization
In recent years, when solving MOPs, especially discrete path optimization problems,
MOACOs concerning other meta-heuristic algorithms have been used and improved often …
MOACOs concerning other meta-heuristic algorithms have been used and improved often …
A decomposition-based many-objective ant colony optimization algorithm with adaptive reference points
H Zhao, C Zhang, B Zhang - Information Sciences, 2020 - Elsevier
The discrete many-objective problem (MaOP) is challenging in practice. Improving the
convergence speed and making the nondominated solutions close to the Pareto front (PF) …
convergence speed and making the nondominated solutions close to the Pareto front (PF) …