Project description
Offering remote earnings. Minimize the transportation task. Need a lecturer in minimization and optimization or a mathematician with experience in the field.
Payment.
By arrangement. Based on the average prices here. Supplement for urgency (up to 08.05).
It is necessary to formalize and solve the problem (preferably in pseudocode or natural language). If it is difficult, it is possible to simply solve mathematical problems.
Description of the task.
Then dot = city.
Data.
Cars.
They have different volumes in conventional units.
Carriers. They have different volumes in y. E.
Cities.
They have coordinates.
Routes.
They're made up of cities. Type: day (from the beginning of the route from 1), time of departure, day and time of arrival. There can be a stop in every city.
Flights.
The truck goes from the starting point of the flight to the final. It is compiled by routes taking into account the date and time of their crossing. There may be overloading of cars between trucks at the point of intersection of routes. In this case, the car is waiting for the designated truck. Planned in advance based on order statistics.
Orders.
The city of departure and arrival. Desirable date of shipment (real date of shipment may be later).
Flight sites
City A-> City B (it is possible to transfer from flight to flight, selection and delivery not only at the starting and end points of one flight)
Statistics. Arrival and departure dates at the points of order. All the other entities described.
It is necessary to make optimal routes and flights on the basis of the collected statistics.
Minimize travel time, overloading of the car and waiting time at the point.
I think it's better to do it using genetic algorithms. You can train on half of the orders, check on the other.
I'll write the program myself. You need an algorithm or a mathematical solution (I think it’s enough).
Payment.
By arrangement. Based on the average prices here. Supplement for urgency (up to 08.05).
It is necessary to formalize and solve the problem (preferably in pseudocode or natural language). If it is difficult, it is possible to simply solve mathematical problems.
Description of the task.
Then dot = city.
Data.
Cars.
They have different volumes in conventional units.
Carriers. They have different volumes in y. E.
Cities.
They have coordinates.
Routes.
They're made up of cities. Type: day (from the beginning of the route from 1), time of departure, day and time of arrival. There can be a stop in every city.
Flights.
The truck goes from the starting point of the flight to the final. It is compiled by routes taking into account the date and time of their crossing. There may be overloading of cars between trucks at the point of intersection of routes. In this case, the car is waiting for the designated truck. Planned in advance based on order statistics.
Orders.
The city of departure and arrival. Desirable date of shipment (real date of shipment may be later).
Flight sites
City A-> City B (it is possible to transfer from flight to flight, selection and delivery not only at the starting and end points of one flight)
Statistics. Arrival and departure dates at the points of order. All the other entities described.
It is necessary to make optimal routes and flights on the basis of the collected statistics.
Minimize travel time, overloading of the car and waiting time at the point.
I think it's better to do it using genetic algorithms. You can train on half of the orders, check on the other.
I'll write the program myself. You need an algorithm or a mathematical solution (I think it’s enough).
Education and consulting Bank transfer
