Problem Statement: We are given an optimisation problem; with production centres, source airport, destination airports, transfer points and finally delivered to the customers. This is better explained in the following picture. Problem Statement

Objective function 1: Minimise costs = inventory costs + transportation costs + penalty costs + loading/unloading costs

  1. Inventory costs = inventory cost at source airport + inventory costs at distribution centres

  2. Transportation costs = cost of transporting cargo from production centre to source airport (via trucks) + cost of transporting cargo through itineraries (via flight) + cost of transporting cargo from distribution centre to transfer points (via trucks) + cost of transporting cargo from transfer point to customers (via drones)

  3. Penalty costs = cost of operating flight routes and delay penalty costs

  4. Loading/unloading costs = cost of loading cargo on trucks at production centres + cost of unloading cargo from trucks at the transfer point

Mathematical Solution (Using IBM CPLEX solver / Docplex): The complete python code (.ipynb file) with the formulation is present in this Google Drive Link. This gives an optimal solution.

Query: Is there any non-mathematical, non-formulation based method to solve this problem statement? Something on the lines of Reinforcement Learning? If any implementation is also provided, it will be icing on the cake.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.