Precalculated Travel Path Routing for Fast Itinerary Search
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Solution Overview
Problem
Online travel search providers face challenges in delivering comprehensive and efficient travel solutions due to reduced interdependence among industry participants, leading to decreased fees and increased computational complexity in finding suitable travel itineraries.
Innovation Solution
A computer-implemented method that periodically calculates potential routings and split points to create theoretical travel paths, generating travel combinations and providing a list of itinerary options by utilizing a processor node, search node, and routing module, which accesses various data sources for flight schedules, fares, and availability data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive travel itineraries are generated by calculating all possible routings and combinations in real-time, then the completeness and accuracy of travel solutions improve, but the computational time and processing complexity increase significantly
Solution Approach 1:
The system performs preliminary calculations of potential routings, split points, and theoretical travel paths before actual travel requests are received. By pre-computing these elements and storing them in a database, the system eliminates the need for exhaustive real-time calculations when processing user requests, thereby maintaining solution accuracy while dramatically reducing response time.
Solution Approach 2:
The travel itinerary generation process is divided into separate computational stages: routing calculation, split point identification, theoretical path creation, and final itinerary assembly. Each stage processes and stores intermediate results independently, allowing the system to reuse pre-computed segments across multiple travel requests without recalculating everything from scratch.
2Adaptability or versatility
If multiple data sources and complex routing calculations are performed for each travel request, then the comprehensiveness of travel options improves, but the device complexity and processing load increase
Solution Approach 1:
The system pre-calculates and stores potential routings, split points, and theoretical travel paths in a database before travel requests are received. This preliminary computation consolidates the complex processing work, allowing the actual travel request handling to simply query and assemble pre-computed results rather than performing exhaustive real-time calculations across multiple data sources.
Solution Approach 2:
A database serves as an intermediary layer between the complex routing calculation engine and the travel request processing system. The database stores pre-computed theoretical travel paths and routing information, acting as a buffer that simplifies the interaction between data sources and request processing, thereby reducing overall system complexity.
3Measurement precision
If real-time calculation of all travel combinations is performed, then the accuracy of fare and availability information improves, but the processing speed and response time decrease
Solution Approach 1:
The system pre-calculates theoretical travel paths, routings, and split points and stores them in a database before actual travel requests are processed. When a travel request is received, the system quickly queries the pre-computed results and performs only minimal fare and availability checks, thereby maintaining information accuracy while achieving fast response times.
Solution Approach 2:
Instead of performing complete real-time validation of all travel combinations, the system performs partial validation by checking only the critical fare and availability information against the pre-computed theoretical paths. This selective approach maintains sufficient accuracy for decision-making while dramatically reducing processing time.
Data Source
AI summary
A system and method to facilitate discovery and reservation of travel options suitably include routing processing, flight selection processing, and fare validation processing. Flight selection processing generates flight combinations for each routing discovered by the routing processing. Not all flight combinations are allowed to proceed thus permitting better flight combinations to emerge. Fare validation processing loads fares, checks availability, and validates them according to the specifics associated with each fare. A list of low cost travel solutions is returned to a travel consumer.