English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

By introducing a quadratic perturbation to the canonical dual of the maxcutproblem, we transform the integer programming problem into a concavemaximization problem over a convex positive domain under some circumstances,which can be solved easily by the well-developed optimization methods.Considering that there may exist no critical points in the dual feasibledomain, a reduction technique is used gradually to guarantee the feasibility ofthe reduced solution, and a compensation technique is utilized to strengthenthe robustness of the solution. The similar strategy is also applied to themaxcut problem with linear perturbation and its hybrid with quadraticperturbation. Experimental results demonstrate the effectiveness of theproposed algorithms when compared with other approaches.

Improved Canonical Dual Algorithms for the Maxcut Problem