Transportation Optimisation

The common modes of freight transport within the country includes trucking (roads), rakes (rail), pressure suction (pipelines), barge (inland waterways) and express (air).

The overall Freight traffic is estimated at 4830 BTKM (Billion Ton-Km) in 2021-22, growing at 1.2x India est. GDP growth until 2031-32 (E).

Road accounts for 50%+ share and, along with Rail, accounts for 86%+ of total Freight movement in BTKM. 

Pipelines have steadily maintained proportionate share while Road, Air and Waterways have been gaining share.

Cost of Air freight is ~10x surface transport and has higher market share than indicated, with larger share of express cargo.

Indian Road Infrastructure

(Source: Basic Road Statistics of India, Ministry of Road Transport and Highways, 2015-16)

India’s length of road infrastructure is 2nd highest amongst nations and behind the USA

63% of roads are paved and a quarter of the National Highways are 4-8 Lane Expressways (NHDP) in FY 2016.

Investment in Highways increased to INR 990 Bn in 2015-16 (US$ 14 B) and expected to accelerate further with PPP projects coming on stream as well – however, there are delays and jury is out on ROI to Concessionaires

Trucking Industry in India

(Source: Category-wise Total Registered Motor Vehicles in India, MORTH, 2015

As on Mar 31, 2015 there were 14.37 mnregistered goods vehicles in India as per the Ministry (MORTH) which has not been updated. There are ~ 0.7 million goods vehicles registered before fiscal year ended Mar 31, 2000. 

The Government proposes to implement BS-IV emission norms by 2020E and not allow trucks over 20 years to ply on Indian roads post Apr 1, 2020. It is estimated that vehicles registered before FY 2000 (pre BS-I) to be 15-25 times more polluting but with secondary and tertiary sales, these trucks keep plying without being scrapped. Hence the need to do so.

Why do we need Optimisation ?

Ask that question to decision makers in FMCG, Retailers and E-Commerce companies and they will wonder which planet you came from 🙂

Optimisers & Solvers

Type of Integer Programming Problems : LP (Continuous, Integer, 0-1, Mixed), Non-LP (Polynomial, General)

Maximise or Minimise Objective Functions

Decision Variables, Constraints

AllocationProblem – deterministic LP where activities assigned on one-to-one basis so as to minimize time, cost or distance ; however, if activities require more than one resource and resources can be used for more than one activity, the allocation problem is classified as a Transportation Problem 

Transportation Problem (Simple, Dual) 

  • Formulate the problem
  • Balanced / Unbalanced (Supply vs Demand)
  • Initial Feasible solution (NWCM, LCM, VAM)
  • Test for optimality (VAM àMODI) : Looping and computing ; rules flip for maximization objective function

When the problem scales, need a solver

  • Established LP packages like QSB+, STORM, LINDO, QSOM etc.
  • Excel / Power BI Solver
  • Gurobi, iLogCPLEX (IBM)

Ultimate Need

Sales & Operations Planning / Demand Planning / Distribution Planning – the dire need of optimisation and visualisation for actionable insights (read: Visilogix)

Concluding Thoughts (on effective use of Optimisation Solvers / Custom Tools)

While the solver is powerful, P <> NP so keep the model simple and parameters limited to prove the concept

  • do not run for all products, 52 time periods, 0-1 decisions at multiple points, etc. at the SAME TIME
  • Set up guardrails before launching into near-infinite loops
  • While speed is important, check bugs before running by thoroughly checking code
  • Use Jenkins or other testing tools (Free, available on cloud) 
  • Solver failure could mean Infeasible Models OR unclean data
  • Swim with data – since one will be spending far more time with data here than the math
  • Use the latest tools even though the transition may be painful, at first. 

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