Liudmila kalashnikova at 22:57, 31 January 2022

2022-01-31T22:57:03Z

Liudmila kalashnikova: Scooter Rental

2022-01-31T22:56:35Z

Scooter Rental

Liudmila kalashnikova at 21:49, 31 January 2022

2022-01-31T21:49:35Z

Liudmila kalashnikova: Created page with "Scooter Rental"

2022-01-31T21:47:55Z

Created page with "Scooter Rental"

New page

Scooter Rental

@@ Line 13: / Line 13: @@
 ----
 The goal of this agent-based simulation is to define optimal number of scooters and service groups for specific city to maximize profit of the company.
-Si,ulation is based on general observation and russian scooter rental market analysis presented by Truesharing ([https://truesharing.ru/tp/28275/ read article]). One tick is considered as one minute, one patch size is 100x100 meters.
+Simulation is based on general observation and russian scooter rental market analysis presented by Truesharing ([https://truesharing.ru/tp/28275/ read article]). One tick is considered as one minute, one patch size is 100x100 meters.
 The simulation has a list of simplifications and limitations; however the overall process looks as folows:
 * On the dashboard it is necessary to set number of scooters, riders and service groups.

← Older revision		Revision as of 22:56, 31 January 2022
Line 1:		Line 1:
−	Scooter ~~Rental~~	+	'''Title''' : Scooter rental
		+	'''Author''' : Liudmila Kalashnikova
		+	'''Methods''': Agent-based modeling
		+	'''Tool''': Netlogo

−	[[File:~~Example~~.~~jpg~~]]	+
		+	'''Problem definition'''
		+	----
		+	Today in almost each big city you can find a huge number of scooters which can be rented. The main feature of scooter rental is that you can take it at one point in the city and return it to another when you finish your route. If there is no scooter nearby, then obviously a potential client will not take it. The more scooters there are in the city, the more chances that people will use this service; however, scooter support also requires additional resources and extra costs.
		+
		+
		+	'''Simulation'''
		+	----
		+	The goal of this agent-based simulation is to define optimal number of scooters and service groups for specific city to maximize profit of the company.
		+	Si,ulation is based on general observation and russian scooter rental market analysis presented by Truesharing ([https://truesharing.ru/tp/28275/ read article]). One tick is considered as one minute, one patch size is 100x100 meters.
		+	The simulation has a list of simplifications and limitations; however the overall process looks as folows:
		+	* On the dashboard it is necessary to set number of scooters, riders and service groups.
		+	* After clicking setup and go buttons. 10% of potential riders will start to look for scooters. Only riders with high propensity_to_rent will go to take the scooter with the speed of 6 km/h.
		+	* After reaching the scooter, the ride starts with the speed of 200 km/h to the end point.
		+	* If the scooter is out of charge, the nearest service group is heading to it. After 45 minutes of recharge, it can be used again.
		+	* The process repeats till the end of simulation. The proposed number of ticks to consider is 132 480 (the number of minutes in summer season).
		+	* The results can be accessed based on monitor and plot for profit.
		+
		+
		+
		+	'''Agents'''
		+	----
		+	Three types of agents are used: Scooters, Riders and Service groups
		+	Scooters
		+	Represent scooters which can be rented. One scooter with maximum charge can work for 3 hours. One minute of riding costs 12 russian roubles. Average speed is 20 km/h Scooters have the following characteristics:
		+	* state - current state of the scooter. Possible options are 1 - available, 2 - rented, 3 - on service, 4 - discharged.
		+	* price - price per minute (12 roubles).
		+	* charge_level - number of minutes used.
		+	* costs - amount of money users paid.
		+	* minutes - total number of minutes in use.
		+
		+	Riders
		+	Represent all people with application for rental. Average speed of walking is 6 km/h. Riders have the following characteristics:
		+	* state - current state of the rider. Possible options are 1 - walking, 2 - going to scooter, 3 - riding.
		+	* scooter_assigned - scooter which was selected in application.
		+	* location_x - x value of the end point of the ride.
		+	* location_y - y value of the end point of the ride.
		+	* propensity_to_rent - propensity of the client to rent a scooter, it depends on distance between rider and potential scooter.
		+
		+	Service groups:
		+	Represent groups of employees which are responsible for charging the vehicles. The costs of 1 charge are 750 roubles. Service groups have the following characteristics:
		+	*state - current state of service groups. Possible options are 1 - don't work at the moment, 2 - on the way to scooter, 3 - work at the moment.
		+	*scooter_assigned - the closest scooter which will be recharged.
		+	*costs - total costs for charging
		+	*item_minutes - number of minutes spent for the current scooter.
		+
		+
		+	'''Results'''
		+	----
		+	To evaluate the results the number of users was fixed to 2000. According to the research of russian scooter market, to serve this number of people it is necessary to have about 200 scooters. Let us check how many service groups is required to maximaze the profit in 1 summer month. With 10 service groups the expected profit is planned to be about 6400000 russian roubles. WIth 20 service groups the estimated profit is about 12000000 russian roubles. With the increase of service groups the number of available scooters also growth in this case. It should be mentioned that the profit is overestimated since not all costs are included.
		+
		+
		+
		+	'''Code'''
		+	----
		+	[[File:Simulation_scooter_rental.nlogo]]

← Older revision		Revision as of 21:49, 31 January 2022
Line 1:		Line 1:
	Scooter Rental		Scooter Rental
		+
		+	[[File:Example.jpg]]

Scooter rental - Revision history

Liudmila kalashnikova at 22:57, 31 January 2022

Liudmila kalashnikova: Scooter Rental

Liudmila kalashnikova at 21:49, 31 January 2022

Liudmila kalashnikova: Created page with "Scooter Rental"