Results 301 to 310 of about 5,359,012 (345)

A Multiform Optimization Framework for Constrained Multiobjective Optimization

IEEE Transactions on Cybernetics, 2022
Constrained multiobjective optimization problems (CMOPs) pose great difficulties to the existing multiobjective evolutionary algorithms (MOEAs), in terms of constraint handling and the tradeoffs between diversity and convergence.
Ruwang Jiao, Bing Xue, Mengjie Zhang
semanticscholar   +1 more source

A Dual-Population-Based Evolutionary Algorithm for Constrained Multiobjective Optimization

IEEE Transactions on Evolutionary Computation, 2021
The main challenge in constrained multiobjective optimization problems (CMOPs) is to appropriately balance convergence, diversity and feasibility. Their imbalance can easily cause the failure of a constrained multiobjective evolutionary algorithm (CMOEA)
Mengjun Ming, Anupam Trivedi, Rui Wang, D. Srinivasan, Tao Zhang   +4 more
semanticscholar   +1 more source

COLSHADE for Real-World Single-Objective Constrained optimization Problems

IEEE Congress on Evolutionary Computation, 2020
In this paper we present the COLSHADE algorithm for real parameter constrained optimization problems. COLSHADE evolved from the basic L-SHADE algorithm by introducing significant features such as adaptive Lévy flights and dynamic tolerance (included in ...
Javier Gurrola-Ramos, A. H. Aguirre, Oscar Dalmau Cedeño   +2 more
semanticscholar   +1 more source

Handling Constrained Multiobjective Optimization Problems via Bidirectional Coevolution

IEEE Transactions on Cybernetics, 2021
Constrained multiobjective optimization problems (CMOPs) involve both conflicting objective functions and various constraints. Due to the presence of constraints, CMOPs’ Pareto-optimal solutions are very likely lying on constraint boundaries.
Zhi-Zhong Liu, Bing-chuan Wang, K. Tang
semanticscholar   +1 more source

Indicator-Based Evolutionary Algorithm for Solving Constrained Multiobjective Optimization Problems

IEEE Transactions on Evolutionary Computation, 2021
To prevent the population from getting stuck in local areas and then missing the constrained Pareto front fragments in dealing with constrained multiobjective optimization problems (CMOPs), it is important to guide the population to evenly explore the ...
Jiawei Yuan, Hai-Lin Liu, Y. Ong, Zhaoshui He   +3 more
semanticscholar   +1 more source

A constrained multi-swarm particle swarm optimization without velocity for constrained optimization problems

Expert systems with applications, 2020
The original particle swarm optimization (PSO) is not able to tackle constrained optimization problems (COPs) due to the absence of constraint handling techniques.
K. M. Ang, W. H. Lim, N. Isa, S. S. Tiang, C. Wong   +4 more
semanticscholar   +1 more source

Butterfly Constrained Optimizer for Constrained Optimization Problems

2018
An extension of the new optimization algorithm, butterfly optimizer (BO) for the constrained optimization problem is discussed in this paper. This version of BO is called butterfly constrained optimizer (BCO) which mimics the mate-locating behaviors of male butterfly and his behavior toward sunspots.
Abhishek Kumar, Tarun Maini, Rakesh Kumar Misra, Devender Singh   +3 more
openaire   +1 more source

Stochastic first-order methods for convex and nonconvex functional constrained optimization

Mathematical programming, 2019
Functional constrained optimization is becoming more and more important in machine learning and operations research. Such problems have potential applications in risk-averse machine learning, semisupervised learning and robust optimization among others ...
Digvijay Boob, Qi Deng, Guanghui Lan
semanticscholar   +1 more source

Data-driven decision making in power systems with probabilistic guarantees: Theory and applications of chance-constrained optimization

Annual Reviews in Control, 2019
Uncertainties from deepening penetration of renewable energy resources have posed critical challenges to the secure and reliable operations of future electric grids.
Xinbo Geng, Le Xie
semanticscholar   +1 more source

The Sailfish Optimizer: A novel nature-inspired metaheuristic algorithm for solving constrained engineering optimization problems

Engineering applications of artificial intelligence, 2019
Nature-inspired optimization algorithms, especially swarm based algorithms (SAs), solve many scientific and engineering problems due to their flexibility and simplicity.
Soodeh Shadravan, Hamid Reza Naji, V. Bardsiri   +2 more
semanticscholar   +1 more source