Figure 1
Figure 2
Figure 3
Figure 4
Average solution values for each instance set (cf_ Fikar and Hirsch, 2015)Tabelle 8_ Durchschnittliche Lösungswerte für jede Testdatenmenge (vgl_ Fikar und Hirsch, 2015)
| Instance set | Average number of scheduled HHC workers | Average vehicle reduction | Average number of pickups | Average portion of driving | Average portion of walking | Average time HHC workers on board or waiting |
|---|---|---|---|---|---|---|
| U-75-24 | 15.2 | -86.8% | 37.6 | 45.6% | 27.2% | 27.2% |
| U-100-32 | 23.2 | -91.4% | 45.0 | 44.1% | 28.5% | 27.4% |
| U-125-40 | 26.4 | -92.4% | 53.0 | 43.8% | 28.8% | 27.4% |
| S-75-24 | 18.2 | -89.0% | 50.6 | 55.2% | 14.3% | 30.4% |
| S-100-32 | 24.8 | -91.9% | 63.4 | 54.3% | 15.3% | 30.4% |
| S-125-40 | 28.0 | -92.9% | 74.8 | 53.1% | 17.3% | 29.5% |
Mobility concepts in HHC and their underlying basic logistical problems (cf_ Voegl and Hirsch, 2015)Tabelle 3_ Mobilitätskonzepte in der mobilen Pflege und ihre grundlegenden logistischen Problemformulierungen (vgl_ Voegl und Hirsch, 2015)
| Mobility concept | DARP | Basic logistical problem VRP | Synchronization | |
|---|---|---|---|---|
| car | individual use | X | ||
| car sharing | X | X | ||
| trip sharing | X | X | ||
| (e-)bike | individual use | X | ||
| (e-)bike sharing | X | X | ||
| walking | X | |||
| taxi use | X | |||
| bus service | X | X | ||
| public transport | no combination | X | ||
| with shared (e-)bikes or cars | X | X | ||
| with individual (e-)bikes or scooters | X |
Solution values [min] for r1, r2, and r3 for different scenarios and the objective functions Λ1 and Λ2 (cf_ Trautsamwieser and Hirsch, 2011)Tabelle 5_ Lösungswerte [min] für r1, r2, und r3 für unterschiedliche Szenarien und Zielfunktionen Λ1 und Λ2 (vgl_ Trautsamwieser und Hirsch, 2011)
| Region | D(Λ1) [min] | D(Λ2) [min] | H1(Λ1) [min] | H1(Λ2) [min] | H2(Λ1) [min] | H2(Λ2) [min] | C(Λ1) [min] | C(Λ2) [min] |
|---|---|---|---|---|---|---|---|---|
| r1 | 171 | 211 | 201 | 255 | 114 | 164 | 155 | 198 |
| r2 | 2,056 | 1,941 | 1,982 | 1,889 | 1,127 | 1,409 | 1,685 | 1,743 |
| r3 | 3,021 | 2,505 | 2,944 | 2,759 | 1,836 | 1,981 | 2,383 | 2,332 |
Weighting of Λ1 and Λ2 (cf_ Trautsamwieser and Hirsch, 2011)Tabelle 6_ Gewichtung von Λ1 und Λ2 (vgl_ Trautsamwieser und Hirsch, 2011)
| Weighting | ||
|---|---|---|
| Part of the objective function | Λ1 | Λ2 |
| total travel time | 1 | 0.5 |
| overtime | 0 | 0.2 |
| preferences | 0 | 0 |
| soft time window violations (job) | 0 | 0.05 |
| soft time window violations (HHC worker) | 0 | 0.05 |
| overqualification | 0 | 0.15 |
| unpaid driving times | 0 | 0.05 |
Commercial logistics versus humanitarian logistics (cf_ Larson, 2014)Tabelle 1_ Vergleich von kommerzieller und humanitärer Logistik (vgl_ Larson, 2014)
| Logistics Context | |||
| Aspect | Commercial | Humanitarian | |
| Purpose | Economic profit | Social impact/Cost recovery | |
| Context | Uninterrupted | Interrupted/Uninterrupted | |
| Perspective on time | “Time is money” | “Time is human health” | |
| People served | Paying customers | Beneficiaries | |
| Source of funds | Paying customers | Donors/Public agencies | |
| Workforce | Paid staff | Volunteers/Paid staff | |
Savings in travel time of HHC workers obtained by TS, TSAS, and TSDYN when compared to the actual planning of the ARC (cf_ Rest and Hirsch, 2016)Tabelle 9_ Einsparungen in der Reisezeit von mobilen Pflegekräften bei Anwendung von TS, TSAS und TSDYN im Vergleich zur aktuellen Planung des Österreichischen Roten Kreuzes (vgl_ Rest und Hirsch, 2016)
| Predefined roster | Flexible working time | |||||
|---|---|---|---|---|---|---|
| Instance | TS | TSAS | TSDYN | TS | TSAS | TSDYN |
| I08 | 37.8% | 37.0% | 34.7% | 50.9% | 50.7% | 51.1% |
| I09 | 29.8% | 29.1% | 28.7% | 46.2% | 46.8% | 46.2% |
| I10 | 40.7% | 38.2% | 40.9% | 56.2% | 55.9% | 57.4% |
| I11 | 51.5% | 51.1% | 47.8% | 59.2% | 58.2% | 59.9% |
| I12 | 40.8% | 34.8% | 38.0% | 52.0% | 52.6% | 52.5% |
| I13 | 49.3% | 48.8% | 48.9% | 54.2% | 53.9% | 54.5% |
| I14 | 48.9% | 47.5% | 48.5% | 57.8% | 56.3% | 57.9% |
| I15 | 61.1% | 60.8% | 59.6% | 65.3% | 64.0% | 65.2% |
| I16 | 37.7% | 34.6% | 37.4% | 40.6% | 39.9% | 40.0% |
| I17 | 45.7% | 41.7% | 45.9% | 51.9% | 51.7% | 52.5% |
| I18 | 34.9% | 33.5% | 34.8% | 38.7% | 37.6% | 38.7% |
| I19 | 35.3% | 35.3% | 34.1% | 44.0% | 42.0% | 44.2% |
| I20 | 26.6% | 23.8% | 23.0% | 40.0% | 43.6% | 44.1% |
| Mean | 41.5% | 39.7% | 40.2% | 50.5% | 50.3% | 51.1% |
Categorization of the author’s publications on HHCTabelle 4_ Kategorisierung der Publikationen des Autors über mobile Pflege
| Publication | Planning horizon | Time-dependent travel times | Solution method | Consideration of disasters | Mode of transport |
|---|---|---|---|---|---|
| Trautsamwieser and Hirsch (2011) | daily | no | metaheuristic (VNS) | no | individual transport mode |
| Trautsamwieser et al. (2011) | daily | no | metaheuristic (VNS) | yes | individual transport mode |
| Rest et al. (2012) | daily | no | metaheuristic (VNS) | yes | individual transport mode |
| Trautsamwieser and Hirsch (2014) | weekly | no | exact (Branch-Price-and-Cut) metaheuristic (VNS) | no | individual transport mode |
| Fikar and Hirsch (2015) | daily | no | Matheuristic | no | bus service |
| Rest and Hirsch (2015) | daily | yes | metaheuristic (TS) | yes | public transport |
| Fikar and Hirsch (2016) | daily | no | metaheuristic (BR) matheuristic | no | individual car use car sharing trip sharing |
| Fikar et al. (2016) | daily | no | metaheuristic (BR) | no | trip sharing |
| Rest and Hirsch (2016) | daily | yes | metaheuristic (TS) | no | public transport |
| Fikar and Hirsch (2017) | Review |
Solution values for an extreme day in three regions with different flood disaster scenarios (cf_ Trautsamwieser et al_, 2011)Tabelle 7_ Lösungswerte für einen Extremtag in den drei Regionen mit verschiedenen Flutszenarien (vgl_ Trautsamwieser et al_, 2011)
| Region | Scenario | # Jobs | # Clients | # HHC workers | Solution value [min] |
|---|---|---|---|---|---|
| θ1 | no flood | 140 | 140 | 13 | 282.70 |
| flood 2002 | 140 | 140 | 13 | 283.20 | |
| HQ200 | 88 | 88 | 10 | 144.00 | |
| θ2 | no flood | 351 | 291 | 39 | 2,435.40 |
| flood 2002 | 299 | 248 | 36 | 1,920.00 | |
| HQ200 | 263 | 218 | 33 | 2,774.10 | |
| θ3 | no flood | 512 | 411 | 75 | 3,497.50 |
| flood 2002 | 504 | 403 | 72 | 3,756.00 | |
| HQ200 | 385 | 307 | 64 | no feasible solution |
Impact of disaster events on HHC (cf_ Rest et al_, 2012)Tabelle 2_ Auswirkungen von Katastrophen auf die mobile Pflege (vgl_ Rest et al_, 2012)
| Disaster event | HHC staff | Clients | transport | Communication | ||
|---|---|---|---|---|---|---|
| Number | Number | Service time | Trafficability | Driving time | Availability | |
| Earthquake | ↓ | ↑ | ↑ | ↓ | ↑ | ↓ |
| Volcano action | ↓ | ↑ | ↑ | ↓ | ↑ | ↓ |
| Mass movement | ↓ | ↑ | ↑ | ↓ | ↑ | ↓ |
| Storm | ↓ | ↑ | ↑ | ↓ | ↑ | ↓ |
| Flood | ↓ | ↑ | ↑ | ↓ | ↑ | ↓ |
| Heat wave | ↓ | ↑ | ↑ | ↔ | ↔ | ↔ |
| Cold wave | ↔ | ↑ | ↑ | ↔ | ↔ | ↔ |
| Epidemic | ↓ | ↑ | ↑ | ↔ | ↔ | ↔ |
| Blackout | ↓ | ↑ | ↑ | ↓ | ↑ | ↓ |