On the Convergence of Pattern Search Algorithms
SIAM Journal on Optimization
Pattern Search Methods for Linearly Constrained Minimization
SIAM Journal on Optimization
Positive Bases in Numerical Optimization
Computational Optimization and Applications
RANK ORDERING AND POSITIVE BASES IN PATTERN SEARCH ALGORITHMS
RANK ORDERING AND POSITIVE BASES IN PATTERN SEARCH ALGORITHMS
GALAHAD, a library of thread-safe Fortran 90 packages for large-scale nonlinear optimization
ACM Transactions on Mathematical Software (TOMS)
A Pattern Search Filter Method for Nonlinear Programming without Derivatives
SIAM Journal on Optimization
Generalized pattern searches with derivative information
Mathematical Programming: Series A and B
Mesh Adaptive Direct Search Algorithms for Constrained Optimization
SIAM Journal on Optimization
Finding Optimal Algorithmic Parameters Using Derivative-Free Optimization
SIAM Journal on Optimization
Convergence of Mesh Adaptive Direct Search to Second-Order Stationary Points
SIAM Journal on Optimization
Using Sampling and Simplex Derivatives in Pattern Search Methods
SIAM Journal on Optimization
Introduction to Derivative-Free Optimization
Introduction to Derivative-Free Optimization
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
The optimal utilization of multiple combined heat and power (CHP) systems is a complex problem. Therefore, efficient methods are required to solve it. In this paper, a recent optimization technique, namely mesh adaptive direct search (MADS) is implemented to solve the combined heat and power economic dispatch (CHPED) problem with bounded feasible operating region. Three test cases taken from the literature are used to evaluate the exploring ability of MADS. Latin hypercube sampling (LHS), particle swarm optimization (PSO) and design and analysis of computer experiments (DACE) surrogate algorithms are used as powerful SEARCH strategies in the MADS algorithm to improve its effectiveness. The numerical results demonstrate that the utilized MADS-LHS, MADS-PSO, MADS-DACE algorithms have acceptable performance when applied to the CHPED problems. The results obtained using the MADS-DACE algorithm are considerably better than or as well as the best known solutions reported previously in the literature. In addition to the superior performance, MADS-DACE provides significant savings of computational effort.