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

This thesis addressed the HHCRSP, which is a class of workforce schedulingproblems. The HHCRSP is an extension of the VRPTW to which the constraintsrelated to the HHC context are added. It aims to provide care services topatients at their homes instead of going to the hospital. We dealt with threedifferent problems from the optimization viewpoint. In the first one, weconsidered a deterministic model to tackle the HHCRSP with multiple timewindows, multiple services, their synchronization if they are required to besimultaneous and skill requirements. We proposed a new mathematical to solvethis problem along with a GVNS based heuristic to solve large instances. In thesecond problem, we extended the deterministic model to cope with uncertaintiesin terms travel and service times. We proposed two SPR models. In the first SPRmodel, we defined the recourse as a penalty cost for the tardiness of servicesand a remuneration for caregivers' overtime. In the second SPR model, wedefined the recourse as skipping patients if their time windows should beviolated. We embedded Monte Carlo simulation, which is used to estimate theexpected value of recourse, into a GA based heuristic to solve SPR models. Inthe last problem, we kept the multi-objective aspect of the deterministic modelwithout aggregating its objective functions, and we used algorithms based onPareto dominance to find the non-dominated solutions and then involve thedecision-maker to select which one he prefers. Two approaches, Pareto anddecomposition based, with multi-objective evolutionary algorithms are adoptedto solve the HHCRSP. Three algorithms are implemented: NSGA-II, MOEA/D and ahybrid NSGA-II with MOEA/D (hybrid) algorithm.

Mathematical models and heuristics for the home health care routing and scheduling problem