Empowering Energy & Resources Workforce Logistics during COVID-19 Disruptions with Mathematical Optimization
Several thousands of workers in oil & gas, mining and construction sectors are stranded at work sites around the world due to the COVID-19 lock down. While companies make the best efforts to protect the health and safety of workers with regular health screenings, reduced essential workforce at project sites, checkerboard seating, limited community interactions, electronic act of acceptance, regular cleaning & disinfecting, seating restrictions during dining etc., it will take several months for the workforce to return to their normal rotating schedule. Many workers are enduring their straight third month of field accommodation at remote camps and offshore installations.
Obviously, companies with robust digital solutions and proper data governance are able to efficiently track down their Personnel on Board (POB) spread across multiple facilities and are in a better position to plan for the best and prepare for the worst. For the oil & gas industry, hit with the double blow of COVID-19 pandemic and historic low oil prices, it remains a significant challenge to efficiently air transport the workforce from worksite to home and back, under unprecedented operational constraints. Cutting-edge logistics optimization technologies can help to overcome these challenges and create sustainable business value. Mathematical optimization provides ample opportunity to resolve highly complex air logistics problems in a faster and efficient manner compared to traditional logistics planning methods.
The new normal for the energy & resources workforce supply chain will witness more operational constraints like reduced logistics budget, blocked middle flight seats, availability of interconnecting commercial/repatriation flights, tightened regulations, healthcare guidelines etc. in addition to traditional constraints of logistics fleet availability, location accessibility, fluctuating demand and weather. In the past, several energy operators have abandoned their mathematical optimization efforts due to the lack of flexibility to handle dynamic operational constraints.
Powerful Mathematical Optimization on Cloud
Modern day optimizers offer a custom layer to fine tune the optimization model on the go by incorporating additional dynamic operational constraints (such as those driven by COVID-19) and adjust configurations in uncertain and challenging times. Advancements in Mixed-Integer Linear Programming (MILP) and cloud computing technology enable faster optimizer performance and make it simple and cost-effective to get powerful optimizations up and running instantly on cloud. Optimizers allow simulation of different scenarios, run them through the solver and review the results instantly. Optimization can be done as often as required, following a SaaS (software as a Service) model. The outputs from multiple scenarios are compared visually over an intuitive web interface for easy decision making. Standard API protocols (REST, SOAP, SFTP, SMTP, HTTPS, JMS) and multiple data exchange formats (XML, JSON and CSV) enable easy integration with third party aviation logistics management systems for automated flight scheduling, passenger seat assignments and email/text confirmation of itinerary.
Key Energy & Resources Questions Answered for the New Normal
- Best aircraft/helicopter fleet mix for maximum demand fulfillment at minimal costs?
- Will adding a new aircraft/helicopter type help?
- Impact on passenger Fly-In Fly-Out (FIFO) rotation schedule?
- Optimized daily flight plan & flight timetable?
The optimized daily flight plan for aircraft and helicopters with the best available fleet mix, taking operational constraints into account, helps to reduce the number of flights and improve seat utilization with zero to minimal adjustments to operational demand. Advanced dashboards and visualizations enable easy simulations and comparison of multiple scenarios for easy decision making. It provides enhanced insights into the logistics planning process and most importantly, provides energy operators, charter airlines and logistics service providers a sustainable return on investment estimated at 15% reduction in monthly flights with an average monthly savings of $500,000 dollars for medium scale operations.
Mathematical optimization models can deliver the most optimal daily flight plan of airplanes and helicopters, which offers the minimal cost and maximum demand fulfillment under a complex set of operational constraints. Technology-aided optimization is no longer optional for energy operators, charter airlines & logistics service providers and COVID-19 will accelerate the path for technology adoption.
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