BOSCH-Route-Optimization

This repository contain code which we submitted for BOSCH Route Optimization at Inter IIT Tech Meet 8.0

Problem Statement

To develop a route optimization algorithm considering following constraints:

• Minimize operational cost.
• Number of buses
• Vehicle occupancy should be at least 85%.
• Time window for pick up and drop off.

Solution Approach

There are two approaches to solve this problem:

• Mathematical Model
• Meta-Heuristic Algorithm

Mathematical Model

Objective: Minimize operational cost Constraints:

• Only one bus will visit one bus stop once in a day.
• Path defining contraints.
• Distance and time limit contraints.
• Capacity and subtour elimination contraints.

Ant Colony Method

• The edge selection is biased towards exploitation (i.e. favoring the probability of selecting the shortest edges with a large amount of pheromone).
• Ants change the pheromone level of the edges they are selecting by applying a local pheromone updating rule
• The best ant is allowed to update the trails by applying a modified global pheromone updating rule.

Content

• Probelem Discription
• Input Data(i.e. Locations)
• Processed data: Distance and Time matrix
• Mathematical Model
• Ant Colony Method
• Presentation