Logistics & Supply Chain
Logistics & Supply Chain
Logistics & Supply Chain
Crew schedule optimization
Crew schedule optimization aims to assign staff to tasks efficiently while meeting regulatory requirements and operational limits. By using advanced algorithms and analysing past data, this process ensures crew members are scheduled effectively, reducing downtime and boosting productivity. Techniques like constraint satisfaction and optimisation algorithms help balance workloads and ensure compliance with labour laws.
Production planning
Optimise manufacturing schedules based on demand forecasts, resource availability, and production capacities. By integrating real-time data and applying optimisation techniques, we help you optimise work processes, minimise downtime, and ensure that production aligns with market needs.
Production planning
Optimise manufacturing schedules based on demand forecasts, resource availability, and production capacities. By integrating real-time data and applying optimisation techniques, we help you optimise work processes, minimise downtime, and ensure that production aligns with market needs.
Production planning
Optimise manufacturing schedules based on demand forecasts, resource availability, and production capacities. By integrating real-time data and applying optimisation techniques, we help you optimise work processes, minimise downtime, and ensure that production aligns with market needs.
Personnel management optimisation
Focus on creating efficient work schedules that align workforce availability with operational demands. By analysing employee skills, preferences, availability, historical performance data, peak store hours, and labour costs, we develop algorithms that ensure optimal crew assignments.
Personnel management optimisation
Focus on creating efficient work schedules that align workforce availability with operational demands. By analysing employee skills, preferences, availability, historical performance data, peak store hours, and labour costs, we develop algorithms that ensure optimal crew assignments.
Personnel management optimisation
Focus on creating efficient work schedules that align workforce availability with operational demands. By analysing employee skills, preferences, availability, historical performance data, peak store hours, and labour costs, we develop algorithms that ensure optimal crew assignments.
Performance monitoring
Put to use KPIs and real-time data analytics to track crew efficiency and productivity. By setting up benchmarks and continuously assessing performance against them, you can identify areas for improvement and carry out targeted strategies.
Performance monitoring
Put to use KPIs and real-time data analytics to track crew efficiency and productivity. By setting up benchmarks and continuously assessing performance against them, you can identify areas for improvement and carry out targeted strategies.
Performance monitoring
Put to use KPIs and real-time data analytics to track crew efficiency and productivity. By setting up benchmarks and continuously assessing performance against them, you can identify areas for improvement and carry out targeted strategies.
Delivery planning
Optimise routing and scheduling for logistics operations to ensure timely and efficient product delivery. By utilising advanced algorithms and geographic information systems (GIS), we analyse factors such as traffic patterns, delivery windows, and vehicle capacities to create optimal delivery schedules.
Delivery planning
Optimise routing and scheduling for logistics operations to ensure timely and efficient product delivery. By utilising advanced algorithms and geographic information systems (GIS), we analyse factors such as traffic patterns, delivery windows, and vehicle capacities to create optimal delivery schedules.
Delivery planning
Optimise routing and scheduling for logistics operations to ensure timely and efficient product delivery. By utilising advanced algorithms and geographic information systems (GIS), we analyse factors such as traffic patterns, delivery windows, and vehicle capacities to create optimal delivery schedules.
Logistics & Supply Chain
Logistics & Supply Chain
Logistics & Supply Chain
Delivery planning
Delivery planning focuses on organising the transportation of goods to ensure timely and cost-effective deliveries. This process uses predictive analytics to forecast demand and optimise routes, considering factors like traffic conditions and delivery windows.
Travel salesman problem
We provide solutions for the Travel Salesman Problem (TSP), aimed at optimising routes for salesmen to minimise travel distance and time. By implementing advanced algorithms, such as genetic algorithms and simulated annealing, we deliver optimal or near-optimal solutions that increase efficiency of your deliveries.
Travel salesman problem
We provide solutions for the Travel Salesman Problem (TSP), aimed at optimising routes for salesmen to minimise travel distance and time. By implementing advanced algorithms, such as genetic algorithms and simulated annealing, we deliver optimal or near-optimal solutions that increase efficiency of your deliveries.
Travel salesman problem
We provide solutions for the Travel Salesman Problem (TSP), aimed at optimising routes for salesmen to minimise travel distance and time. By implementing advanced algorithms, such as genetic algorithms and simulated annealing, we deliver optimal or near-optimal solutions that increase efficiency of your deliveries.
Vehicle routing problem
We provide solutions for the vehicle routing problem (VRP) using optimisation techniques to identify the most efficient routes for different delivery drivers, each facing unique challenges. By carefully analysing various factors—including delivery locations, vehicle capacities, and customer preferences—we work out routes that minimise travel time and fuel consumption while making sure to fit other requirements.
Vehicle routing problem
We provide solutions for the vehicle routing problem (VRP) using optimisation techniques to identify the most efficient routes for different delivery drivers, each facing unique challenges. By carefully analysing various factors—including delivery locations, vehicle capacities, and customer preferences—we work out routes that minimise travel time and fuel consumption while making sure to fit other requirements.
Vehicle routing problem
We provide solutions for the vehicle routing problem (VRP) using optimisation techniques to identify the most efficient routes for different delivery drivers, each facing unique challenges. By carefully analysing various factors—including delivery locations, vehicle capacities, and customer preferences—we work out routes that minimise travel time and fuel consumption while making sure to fit other requirements.
Capacity optimisation
Ensure that transportation and storage resources are utilised to their fullest potential. By analysing historical usage data and demand forecasts, we develop strategies to allocate resources efficiently across the supply chain, preventing underutilisation and overcapacity.
Capacity optimisation
Ensure that transportation and storage resources are utilised to their fullest potential. By analysing historical usage data and demand forecasts, we develop strategies to allocate resources efficiently across the supply chain, preventing underutilisation and overcapacity.
Capacity optimisation
Ensure that transportation and storage resources are utilised to their fullest potential. By analysing historical usage data and demand forecasts, we develop strategies to allocate resources efficiently across the supply chain, preventing underutilisation and overcapacity.
Time-window constraints optimisation
Focus on developing schedules that fit into specific delivery time windows. By employing constraint programming and optimisation algorithms, we ensure that deliveries are made within required time frames while maximising overall efficiency.
Time-window constraints optimisation
Focus on developing schedules that fit into specific delivery time windows. By employing constraint programming and optimisation algorithms, we ensure that deliveries are made within required time frames while maximising overall efficiency.
Time-window constraints optimisation
Focus on developing schedules that fit into specific delivery time windows. By employing constraint programming and optimisation algorithms, we ensure that deliveries are made within required time frames while maximising overall efficiency.
Resource optimisation
Make use of data analytics and modelling techniques to effectively allocate resources across multiple capacity entities within various logistics operations. By examining factors such as demand variability, workforce availability, vehicle capacities, and storage limitations, we create strategies that ensure optimal resource allocation.
Resource optimisation
Make use of data analytics and modelling techniques to effectively allocate resources across multiple capacity entities within various logistics operations. By examining factors such as demand variability, workforce availability, vehicle capacities, and storage limitations, we create strategies that ensure optimal resource allocation.
Resource optimisation
Make use of data analytics and modelling techniques to effectively allocate resources across multiple capacity entities within various logistics operations. By examining factors such as demand variability, workforce availability, vehicle capacities, and storage limitations, we create strategies that ensure optimal resource allocation.
Logistics & Supply Chain
Logistics & Supply Chain
Logistics & Supply Chain
Vehicle pathfinding for road network
On extensive road networks, even huge ones like across Western Europe, finding the shortest path from a starting point to a destination can be done quickly. By examining factors like road conditions, traffic patterns, and vehicle capabilities, we can offer optimal routing solutions.
Arrival time optimisation
Bring into play real-time traffic data and predictive analytics to enhance the accuracy of estimated arrival times. By analysing factors such as current traffic conditions, road types, and historical travel times, we develop algorithms that offer optimal routing suggestions.
Arrival time optimisation
Bring into play real-time traffic data and predictive analytics to enhance the accuracy of estimated arrival times. By analysing factors such as current traffic conditions, road types, and historical travel times, we develop algorithms that offer optimal routing suggestions.
Arrival time optimisation
Bring into play real-time traffic data and predictive analytics to enhance the accuracy of estimated arrival times. By analysing factors such as current traffic conditions, road types, and historical travel times, we develop algorithms that offer optimal routing suggestions.
Traffic jams forecasting
Take advantage of machine learning models to predict traffic congestion based on historical data, weather conditions, and real-time traffic reports. By analysing patterns and trends, we provide actionable understanding that help logistics companies adjust their routes and schedules.
Traffic jams forecasting
Take advantage of machine learning models to predict traffic congestion based on historical data, weather conditions, and real-time traffic reports. By analysing patterns and trends, we provide actionable understanding that help logistics companies adjust their routes and schedules.
Traffic jams forecasting
Take advantage of machine learning models to predict traffic congestion based on historical data, weather conditions, and real-time traffic reports. By analysing patterns and trends, we provide actionable understanding that help logistics companies adjust their routes and schedules.
Delay management
Focus on identifying, monitoring, and mitigating delays in the transportation process. By using real-time tracking and analytics, we provide alerts for potential disruptions and recommend alternative routes or strategies to minimise impact.
Delay management
Focus on identifying, monitoring, and mitigating delays in the transportation process. By using real-time tracking and analytics, we provide alerts for potential disruptions and recommend alternative routes or strategies to minimise impact.
Delay management
Focus on identifying, monitoring, and mitigating delays in the transportation process. By using real-time tracking and analytics, we provide alerts for potential disruptions and recommend alternative routes or strategies to minimise impact.
Logistics & Supply Chain
Logistics & Supply Chain
Logistics & Supply Chain
Transit pathfinding for public transport
Transit pathfinding for public transport optimises routes and schedules for buses, trains, and other public transport systems. Public transport networks can be represented as graphs, similar to road networks, meaning that many road-routing algorithms can also be used for public transport. However, these algorithms typically do not perform as efficiently. Currently, we lack methods to route public transport networks as quickly as we can for large road networks. Recently, more advanced solutions like CSA (Contracted Shortest Path Algorithms) and RAPTOR (Real-time Adaptive Pathfinding for Transit Operations Research) have significantly enhanced search capabilities in transport networks.
Arrival time optimisation
Make use of real-time data and predictive algorithms to enhance the accuracy of estimated arrival times for public transport systems. By integrating data from GPS tracking, historical travel patterns, and current traffic conditions, we develop models that adjust routes dynamically.
Arrival time optimisation
Make use of real-time data and predictive algorithms to enhance the accuracy of estimated arrival times for public transport systems. By integrating data from GPS tracking, historical travel patterns, and current traffic conditions, we develop models that adjust routes dynamically.
Arrival time optimisation
Make use of real-time data and predictive algorithms to enhance the accuracy of estimated arrival times for public transport systems. By integrating data from GPS tracking, historical travel patterns, and current traffic conditions, we develop models that adjust routes dynamically.
Journey planner
Help passengers navigate public transport networks seamlessly. By analysing various routes, schedules, and transfer points, we provide users with optimised travel itineraries that minimise travel time and maximise convenience, while taking into account real-time service updates, disruptions, and user preferences.
Journey planner
Help passengers navigate public transport networks seamlessly. By analysing various routes, schedules, and transfer points, we provide users with optimised travel itineraries that minimise travel time and maximise convenience, while taking into account real-time service updates, disruptions, and user preferences.
Journey planner
Help passengers navigate public transport networks seamlessly. By analysing various routes, schedules, and transfer points, we provide users with optimised travel itineraries that minimise travel time and maximise convenience, while taking into account real-time service updates, disruptions, and user preferences.
Multimodal transport optimisation
Integrate various transport modes—such as buses, trains, and cycling—into cohesive travel plans. By using optimisation algorithms that consider factors like travel times, transfer times, and costs, we provide passengers with efficient and flexible travel options reliable across different environments.
Multimodal transport optimisation
Integrate various transport modes—such as buses, trains, and cycling—into cohesive travel plans. By using optimisation algorithms that consider factors like travel times, transfer times, and costs, we provide passengers with efficient and flexible travel options reliable across different environments.
Multimodal transport optimisation
Integrate various transport modes—such as buses, trains, and cycling—into cohesive travel plans. By using optimisation algorithms that consider factors like travel times, transfer times, and costs, we provide passengers with efficient and flexible travel options reliable across different environments.
Logistics & Supply Chain
Logistics & Supply Chain
Logistics & Supply Chain
Vessel navigation
Vessel navigation systems optimise routing based on factors such as weather conditions, sea currents, and port regulations. Standard algorithms used for finding paths in 2D space have limitations when applied to the Earth's scale, because the shortest path on a sphere isn't a straight line. So we can adapt existing algorithms to meet the needs of the maritime industry.
Arrival time optimisation
During predicting when a vessel will reach its destination, you need to consider factors like weather conditions, sea currents, and port traffic. By using advanced algorithms and real-time data, we optimise your routing options while considering such variables as vessel speed and operational limits.
Arrival time optimisation
During predicting when a vessel will reach its destination, you need to consider factors like weather conditions, sea currents, and port traffic. By using advanced algorithms and real-time data, we optimise your routing options while considering such variables as vessel speed and operational limits.
Arrival time optimisation
During predicting when a vessel will reach its destination, you need to consider factors like weather conditions, sea currents, and port traffic. By using advanced algorithms and real-time data, we optimise your routing options while considering such variables as vessel speed and operational limits.
Fuel consumption modelling
Make use of advanced simulation techniques and historical operational data to predict fuel usage for vessels under various conditions. By analysing factors such as vessel speed, cargo load, weather patterns, and sea currents, we develop comprehensive models that provide accurate estimates of fuel consumption.
Fuel consumption modelling
Make use of advanced simulation techniques and historical operational data to predict fuel usage for vessels under various conditions. By analysing factors such as vessel speed, cargo load, weather patterns, and sea currents, we develop comprehensive models that provide accurate estimates of fuel consumption.
Fuel consumption modelling
Make use of advanced simulation techniques and historical operational data to predict fuel usage for vessels under various conditions. By analysing factors such as vessel speed, cargo load, weather patterns, and sea currents, we develop comprehensive models that provide accurate estimates of fuel consumption.
Fuel optimisation
Leverage AI-driven analytics to automate route and speed adjustments based on real-time conditions. By employing algorithms that analyse fuel consumption patterns and operational metrics, we help you identify the most efficient navigation strategies.
Fuel optimisation
Leverage AI-driven analytics to automate route and speed adjustments based on real-time conditions. By employing algorithms that analyse fuel consumption patterns and operational metrics, we help you identify the most efficient navigation strategies.
Fuel optimisation
Leverage AI-driven analytics to automate route and speed adjustments based on real-time conditions. By employing algorithms that analyse fuel consumption patterns and operational metrics, we help you identify the most efficient navigation strategies.
Let's talk with our CEO
Email: andrii.rohovyi@postdata.ai
Let's talk with our CEO
Email: andrii.rohovyi@postdata.ai
Let's talk with our CEO
Email: andrii.rohovyi@postdata.ai
Postdata. All right reserved. © 2024
Postdata. All right reserved. © 2024
Postdata. All right reserved. © 2024