Travel Accommodation Selection via Preference Optimization
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Solution Overview
Problem
Current online reservation systems lack the ability to effectively customize and optimize travel accommodations based on user preferences, leading to suboptimal selection of seats or accommodations during travel reservations.
Innovation Solution
A system that includes a property customization module for receiving user input to customize software travel objects representing accommodations, an interface for specifying preferences, and an optimization function to weight and compare these preferences with the customized properties to select suitable accommodations, allowing users to choose the best fit for their needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional online reservation systems are used to search for available seats, then basic seat availability can be determined, but the system cannot effectively customize and optimize travel accommodations based on user preferences
Solution Approach 1:
The system segments the accommodation selection process into distinct components: a property customization module that defines configurable attributes of travel objects, an interface that collects user preferences, and an optimization function that processes the data. This segmentation allows each component to specialize in one aspect, improving overall adaptability while managing complexity through modular design.
Solution Approach 2:
The system enables dynamic parameter changes by allowing users to specify and weight multiple criteria (such as seating direction, ambience, location) that can be adjusted and reweighted. The optimization function processes these parameter changes to generate customized accommodation recommendations, thereby enhancing adaptability without requiring complete system redesign.
2Manufacturing precision
If the system includes multiple modules for customization and optimization, then accommodation selection quality improves, but the system complexity increases
Solution Approach 1:
The optimization function serves multiple purposes: it weights user criteria, compares weighted criteria against customized properties, selects accommodations that satisfy the optimization function, and outputs results for user selection. This multi-functionality improves selection accuracy while avoiding the need for separate specialized modules for each task, thereby managing system structure complexity.
Solution Approach 2:
The property customization module performs preliminary action by pre-defining configurable properties of travel objects before the actual reservation process. This preliminary configuration establishes the framework for subsequent optimization, improving selection accuracy by ensuring all relevant attributes are considered while reducing real-time processing complexity.
3Adaptability or versatility
If the system processes multiple user criteria with weighting, then the ability to match user preferences improves, but the processing time and computational requirements increase
Solution Approach 1:
The system implements partial action by allowing users to specify only the most important criteria and weightings rather than requiring complete detailed preferences. The optimization function processes this subset of criteria first, providing quick initial recommendations that can be refined if needed, thereby improving preference matching while minimizing processing time through selective rather than exhaustive analysis.
Data Source
AI summary
The subject matter of this specification can be embodied in, among other things, a process that includes selecting accommodations during a travel reservation is described. The method includes receiving, at a software application that manages travel reservations, input that customizes configurable attributes of software travel objects representing accommodations used in transportation of passengers. The method also includes receiving criteria from a customer specifying preferences that affect a passenger's experience during travel, ranking the received criteria so that one or more criterion are preferred, selecting one or more of the accommodations using an optimization function to compare the ranked criteria to the customized configurable attributes, and outputting the selected one or more accommodations for use by the customer in selecting a first accommodation for the passenger.