Differential evolution with multi-constraint consensus methods for constrained optimization

DOI10.1007/s10898-012-9987-zzbMath1315.90019OpenAlexW2088720805MaRDI QIDQ377757

Noha M. Hamza, Ruhul A. Sarker, Daryl L. Essam

Publication date: 7 November 2013

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10898-012-9987-z

zbMATH Keywords

constrained optimizationevolutionary algorithmsdifferential evolutionconstraint consensus

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Management decision making, including multiple objectives (90B50) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• CEC 05

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Multi-operator based evolutionary algorithms for solving constrained optimization problems
• Differential evolution. A practical approach to global optimization. With CD-ROM.
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• An efficient constraint handling method for genetic algorithms
• The least-intensity feasible solution for aperture-based inverse planning in radiation therapy
• Improving solver success in reaching feasibility for sets of nonlinear constraints
• The Constraint Consensus Method for Finding Approximately Feasible Points in Nonlinear Programs
• Making a Difference to Differential Evolution
• Production scheduling/rescheduling in flexible manufacturing
• Historical Development of the Newton–Raphson Method
• Component averaging: An efficient iterative parallel algorithm for large and sparse unstructured problems