Erratum: Adjustable Constrained Soft‐Tissue Dynamics

Difficulty Adjustable and Scalable Constrained Multi-objective Test Problem Toolkit

In order to better understand the advantages and disadvantages of a constrained multi-objective evolutionary algorithm (CMOEA), it is important to understand the nature of difficulty of a constrained multi-objective optimization problem (CMOP) that the CMOEA is going to deal with. A CMOP includes objectives and constraints, and a number of features, such as the multi-modality and the degeneracy...

An Adjustable Chance-Constrained Approach for Flexible Ramping Capacity Allocation

With the fast growth of wind power penetration, power systems need additional flexibility to cope with wind power ramping. Several electricity markets have established requirements for flexible ramping capacity (FRC) reserves. This paper addresses two crucial issues that have rarely been discussed in the literature: 1) how to characterize wind power ramping under different forecast values and 2...

Erratum

Erratum: Mesh Adaptive Direct Search Algorithms for Constrained Optimization

In [SIAM J. Optim., 17 (2006), pp. 188-217] Audet and Dennis proposed the class of mesh adaptive direct search algorithms (MADS) for minimization of a nonsmooth function under general nonsmooth constraints. The notation used in the paper evolved since the preliminary versions and, unfortunately, even though the statement of Proposition 4.2 is correct, is not compatible with the final notation. ...

Erratum to: Adaptive matching pursuit with constrained total least squares

After publication of our work [1], we noticed that equations (41) and (42) (in Appendix 1) were incorrect. This does not affect resulting equations. The correct equations are below: