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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.

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