| Roll Number | Name |
|---|---|
| 18EE10025 | Yash Kulkarni |
| 18EE10043 | Rhitvik Sinha |
| 18EE30021 | Pratyush Jaiswal |
| 18EE30029 | Nuruddin Jiruwala |
Electric Vehicle
Consider a city network where we need to route a set of electric vehicles
which may require to be charged during its journey from some source to some destination. Let
us assume that we have n cities (v1, v2, . . . , vn) and the distance between cities vi and vj be
eij (if two cities are not connected directly then eij = ∞ and eij = eji). Assume that each city
has a single charging station which can charge one EV at a time. Consider a set of k EVs namely
P1, P2, . . . , Pk. For each EV the following information is provided -
(a) Sr - source node
(b) Dr - destination node
(c) Br - battery charge status initially
(d) cr - charging rate for battery at a charging station (energy per unit time)
(e) dr - discharging rate of battery while traveling (distance travel per unit charge)
(f) Mr - maximum battery capacity
(g) sr - average traveling speed (distance per unit time).
Assume that all vehicles start their journey at t = 0 and Pr reaches it destination at t = Tr. We
need to route all the vehicles from their respective sources to destinations such that max{Tr}
is minimized. You need to develop both optimal as well as heuristic algorithms.
- Python 3.X is used. Download here
- Source Code here.
- User Manual / Report here. Or view on Google Docs.