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

The problem of task scheduling with communication delays is strongly NP-hard.State-space search algorithms such as A* have been shown to be a promisingapproach to solving small to medium sized instances optimally. A recentlyproposed state-space model for task scheduling, known as Allocation-Ordering(AO), allows state-space search methods to be applied without the need forpreviously necessary duplicate avoidance mechanisms, and resulted insignificantly improved A* performance. The property of a duplicate-free statespace also holds particular promise for memory limited search algorithms, suchas depth-first branch-and-bound (DFBnB), and parallel search algorithms. Thispaper investigates and proposes such algorithms for the AO model and, forcomparison, the older Exhaustive List Scheduling (ELS) state-space model. Ourextensive evaluation shows that AO gives a clear advantage to DFBnB and allowsgreater scalability for parallel search algorithms.

Parallel and Memory-limited Algorithms for Optimal Task Scheduling Using a Duplicate-Free State-Space