Enabled a leading IT company to predict operations accurately and predicting the service cost

Maximizing Profits with Route Optimization Analytics

Case Study: Maximizing Profits with Route Optimization Analytics

About the Client

The client is a leading oil and gas public-sector company based in India. In addition, the client also deals with the entire hydrocarbon value-chain that includes pipeline transportation, refining, petroleum product marketing, crude oil exploration and production, petrochemicals, and natural gas. Furthermore, the client, being the largest commercial oil company in the country has foreign subsidiaries as well.

The Business Challenge

We built an IT Operations Analytics tool that will give the client access to accurate dashboards, predictive pricing, and predictive analytics.

What Aptus Data Labs Did

We devised and built a time-series forecasting analytics tool to allocate the number of TC (time-charted ships) and VC (voyage-chartered ships) in an optimized way.

The Impact Aptus Data Labs Made

The supply chain scheduling and route optimization tool helped the client to schedule the voyages accurately. Additionally, the client was also able to reduce the logistics costs of the charter assignment.

The Business and Technology Approach

Aptus Data Labs used the following process to build a supply chain scheduling and route optimization tool to resolve the business challenge.

  • Devised and built a heterogeneous resource allocation algorithm to allocate and optimize the number of TC and VC ships
  • Cleansed and prepared historical data for processing
  • Used historical data and Holt-Winters algorithm to forecast by time-series analysis and overcome the model’s seasonality effect
  • Enabled linear distribution of the voyages in the model
  • Calculated the posterior probability of each voyage trip in a given month using
  • Used the resulting probability to determine future voyages
  • Calculated the corresponding TC cost, VC cost, and the number of days of the round trip journey based on the determined voyages
  • Fed the determined values to the algorithm to allocate the number of TC and VC to minimize the total charter

Tools used

  • R
  • RapidMiner
  • Oracle Database

The Outcome

The supply chain scheduling and route optimization analytics solution helped the client to predict the schedule for voyages for the following year efficiently. Moreover, the client was able to minimize the total charter cost by planning and strategizing based on the predictive results. Therefore, the client was also able to fully automate the voyage schedule generation reducing manual workforce and resources.

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