Delivery Assistance System for Joint Delivery Constraint Optimization
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Solution Overview
Problem
In joint delivery systems, the importance of constraint conditions varies among different players, necessitating adjustments to optimize delivery processes.
Innovation Solution
A delivery assistance system that acquires condition values for various constraint conditions, estimates index values related to joint delivery, identifies constraint conditions where index value variations meet predetermined criteria, and presents these findings to users for adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If constraint conditions are adjusted to optimize joint delivery, then delivery process optimization improves, but the complexity of coordinating multiple players with different importance levels increases
Solution Approach 1:
The system introduces an intermediary platform that mediates between multiple consignors and distribution companies. This platform collects constraint conditions from all players, performs centralized analysis to identify critical constraints, and provides coordinated adjustment recommendations. The intermediary resolves the coordination complexity by centralizing the decision-making process while allowing individual players to maintain their specific requirements.
Solution Approach 2:
The system changes the parameters of constraint conditions by analyzing their importance levels and variations across different players. It identifies which constraint parameters (delivery dates, locations, load amounts) have the greatest impact on joint delivery optimization and adjusts these parameters systematically. This approach transforms the complex multi-player coordination problem into a manageable parameter optimization problem.
2Adaptability or versatility
If constraint condition adjustments are made to accommodate all players, then satisfaction of individual requirements improves, but the difficulty of finding optimal joint delivery plans increases
Solution Approach 1:
The system segments the overall joint delivery optimization problem into individual constraint condition analyses. It evaluates each constraint condition separately, determining its importance level and potential for adjustment. This segmentation allows the system to handle multiple players' requirements systematically by addressing each constraint independently before synthesizing the overall optimization strategy.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring constraint condition variations and their impacts on joint delivery plans. It provides feedback to players about how their constraint adjustments affect overall optimization, enabling iterative refinement of delivery plans. This feedback loop helps resolve the difficulty of finding optimal plans by guiding the search process based on observed outcomes.
Data Source
AI summary
A delivery assistance system comprising: a memory storing instructions; and at least one processor configured to execute the instructions to: acquire a condition value of each of a plurality of constraint conditions related to joint delivery; estimate an index value, of an index related to joint delivery, for the acquired condition value and an index value of the index in a case where the acquired condition value is changed for each of the plurality of constraint conditions; identify a constraint condition in which a variation of the estimated index values meets a predetermined criterion among the plurality of constraint conditions; and present the identified constraint condition and the variation of the index values to a user.