University of Twente Student Theses
Distributing Police vehicles across Noord-Holland : distributing emergency and civilian vehicles to maximise the mobility
Hoek, Tom (2018) Distributing Police vehicles across Noord-Holland : distributing emergency and civilian vehicles to maximise the mobility.
|
PDF
2MB |
| Abstract: | This research considers the distribution of emergency and civilian vehicles for the Unit of Noord Holland. The Unit is reorganising the teams, the offices and as a result, also it’s vehicles. The vehicles are tools to provide mobility to the Unit. This leads to the following research question: How should the Unit of Noord-Holland redistribute its vehicles across Noord-Holland, to maximize its mobility? Two types of vehicles are considered in this research: Emergency and Civilian. Within the current fleet, four vehicle categories have been defined: Civilian, Striped, Specialized and Covert vehicles. The striped vehicles have been categorized further into seven subcategories, one of which containing the Emergency vehicles. The other vehicles are not considered, covert vehicles have to remain covert, specialized vehicles are dedicated to specialised tasks, fixing the distribution decision, and the six other subcategories are also dedicated to specialised tasks. Maximising the mobility for emergency vehicles means maximizing the percentage of handling incidents in-time. Within 15 minutes for priority 1 and 30 minutes for priority two, while also handling priority three incidents. Maximising the mobility for civilian vehicles means minimising the probability of having to wait for a vehicle, for all teams equally. The Unit wants to gain insight on the effects of vehicle pooling, assign vehicle to teams or pool vehicles at offices, and on the effects of having dedicated vehicles for standby-services or not. Emergency vehicles: For emergency vehicles, a distribution model, based on Daskin’s MEXCLP1, is used allocating all vehicles (125 for 10 Base Teams) to a node. The area of the Unit has been divided into 4322 nodes, each node having an expected demand of priority one, two and three incidents. Depending on the average speed per BT, a coverage matrix is used to decide whether a vehicle is able to cover the distance between two nodes in-time. Each vehicle is expected to be busy 23% of the time. A vehicle allocated to a node, is able to service 77% of the incidents in-time, that it can reach in-time, from that node. Multiple vehicles covering the same node lead to a higher percentage of incidents covered on that node. The emergency distribution result has been verified using simulation. Within the simulation a more realistic process flow is used, incorporating vehicle assignment decisions to priority incidents and allowing for incidents being interrupted or having to wait. Equal demand per hour and the more realistic demand variation per hour show the same results as the distribution: 0 are not serviced in-time and 0 incidents are interrupted. This is better than a random allocation, 48% not serviced in-time and 6% interrupted, and when allocating vehicles at office locations, 20% not serviced in-time and 9% interrupted. Civilian vehicles: For civilian vehicles, a queuing model is used to distribute vehicles (311 vehicles) across teams and locations2. Four scenarios are considered: 1) team vehicles and dedicated standby-services vehicles, 2) team vehicles incorporating standby-services, 3) location pools and dedicated standby-services vehicles and 4) location pools incorporating standby-services. Distributions are based on the arrival rate, service rate and FTE, either per team or aggregated to a location. Each team or location is handled as an M/M/c/K-queue. Vehicles are iteratively assigned to queues that have the highest probability of having to wait. Civilian vehicle distribution result has been verified using simulation. Within the simulation a more realistic process flow and workday shift is used3. The workdays cause any existing queues to reset every weekday and leads to the following results in waiting probabilities: 1) 2.5%, 2) 1.8%, 3) 0.05% and 4) 0.03% and average waiting times of: 1) 298.2 seconds, 2) 164.5 seconds, 3) 0.7 seconds and 4) 0.5 seconds. Advice: To maximise the mobility the Unit should distribute the emergency vehicles to the Base Teams as shown in Table 1 and for civilian vehicles, pool vehicles at office locations and supply standby-service demand from these pools. Table 1: Vehicle allocations per Base Team: shows the number of vehicles assigned to each Base Team. Emergency vehicles are not the bottleneck for incidents, consider further research into factors affecting response-times and the use of vehicle distribution models as a tool for the DROC4, considering the provided coverage. The available set of civilian vehicles should be able to handle all demand. Look for a fitting vehicle sharing system, that will provide access to all employees and that does not tie up vehicles in unnecessary reservations. Monitor the use of all vehicles in order to improve the fit of available vehicles to the needs of the Unit. |
| Item Type: | Essay (Master) |
| Clients: | Politie Eenheid Noord Holland, Haarlem, Nederland |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 85 business administration, organizational science |
| Programme: | Industrial Engineering and Management MSc (60029) |
| Link to this item: | https://purl.utwente.nl/essays/76329 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page