H9MSO The map of the city in figure is generated using a python scripts Generate Data: Modeling, Simulation & Optimization Assignment, NCI, Ireland
| University | National College of Ireland (NCI) |
| Subject | Simulation & Optimization Assignment. |
2 General input information and constraints
In order to perform the initial study, a list of information is collected:
• A map M of the township with customer locations C. Figure 1 shows an example with 100 customer locations. The map of the city in figure is generated using a python scripts Generate Data. ipynb which contains a method generateData which can be used to generate other sample data.
• An estimated average number 𝑝 of parcels within the range 0.3 ≤ 𝑝 ≤ 0.4. The interarrival time for parcels for a given customer is an independent expovariate distribution with 𝜇 = 1/𝑝. During Christmas the rate increase to .6.
• The company has a choice between electric cargo bikes with a range of 30, 35, 40 or 45km. The company wants to test the business idea with the cheapest possible bike and the price of the bike grows substantially with the range. This means that you can not have tours that bigger than the maximum range
• The delivery driver has a planned average working time of 3 hours per working day (18:00-21:00). Between 09:00 and 17:00, the Warehouse receive packages which the deliverer prepares before starting the delivery. If a cargo bike with 40km range, the delivery might exceed three hours per day, so this is a soft constraint.
• The time required for driving can be estimated based on the path length between any
two points at an average speed of 15km/h.
• The time for handing over the parcels to the customer consists of a call time (for the customer to come to the door) that follows an expovariate distribution with a mean time of 40sec) and an additional handover time per parcel, which again follows an exponential distribution with on average 10s per parcel.
• The cumulative preparation time (route planning and sorting of the parcels in the delivery order and packing the cargo-bike) is assumed to be 50 sec per parcel to be delivered.
• The day-end procedure (reporting and setting up the cargo-bike for charging) is 10 minutes.
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