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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Viability of electric car-sharing operations depends on rebalancingalgorithms. Earlier methods in the literature suggest a trend toward non-myopicalgorithms using queueing principles. We propose a new rebalancing policy usingcost function approximation. The cost function is modeled as a p-medianrelocation problem with minimum cost flow conservation and path-based chargingstation capacities on a static node-charge graph structure. The cost functionis NP-complete, so a heuristic is proposed that ensures feasible solutions thatcan be solved in an online system. The algorithm is validated in a case studyof electric carshare in Brooklyn, New York, with demand data shared from BMWReachNow operations in September 2017 (262 vehicle fleet, 231 pickups per day,303 traffic analysis zones (TAZs)) and charging station location data (18charging stations with 4 port capacities). The proposed non-myopic rebalancingheuristic reduces the cost increase compared to myopic rebalancing by 38%.Other managerial insights are further discussed.

A node-charge graph-based online carshare rebalancing policy with capacitated electric charging