Transportation Plan Scheduling With Minimum Occupancy Constraints
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Solution Overview
Problem
Existing demand bus services struggle to maintain profitability in areas with low transportation request density, as vehicle sharing is not established, and the operation status resembles that of a taxi at a lower fare, making it difficult to sustain business profitability.
Innovation Solution
An information processing method that creates a provisional transportation plan by allocating multiple customers to vehicles based on predetermined constraint conditions, including minimum occupancy and time ratios, to ensure profitability, and notifies customers of their travel schedules or rejections in advance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If demand bus service operates in low-density areas with individual customer transportation, then customer service availability is improved, but transportation profitability deteriorates due to insufficient vehicle sharing
Solution Approach 1:
The system performs preliminary actions by collecting transportation requests in advance and creating provisional transportation plans before the service period begins. The management server accumulates requests from multiple customers and pre-calculates optimal vehicle allocations, ensuring that even in low-density areas, vehicles are efficiently utilized when sufficient requests are gathered. This preliminary planning enables the system to guarantee minimum occupancy thresholds before deployment, thereby maintaining profitability while preserving service availability.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring transportation request density and vehicle utilization rates. When request density falls below thresholds necessary for profitable operation, the system provides feedback to adjust service parameters, such as consolidating routes, adjusting pricing, or modifying vehicle allocation strategies. This feedback loop enables dynamic adaptation to maintain profitability while preserving service availability in low-density areas.
2Productivity
If minimum occupancy constraints are enforced to ensure profitability, then transportation profitability is improved, but service flexibility deteriorates
Solution Approach 1:
The system applies dynamics by making occupancy constraints flexible rather than rigid. The management server dynamically adjusts minimum occupancy thresholds based on real-time request density, vehicle availability, and route characteristics. When request density is high, stricter occupancy constraints can be enforced to maximize profitability. When density is low, the system relaxes constraints or consolidates multiple requests to achieve minimum thresholds, thereby maintaining service flexibility while ensuring profitability through adaptive rather than fixed occupancy rules.
3Speed
If real-time transportation plan creation is implemented, then response speed to new requests is improved, but computational complexity increases
Solution Approach 1:
The system reduces computational complexity during real-time operation by performing preliminary calculations in advance. The management server pre-processes transportation requests, pre-calculates optimal routes, and pre-determines vehicle allocations before the service period begins. This preliminary action creates a ready-to-execute framework that requires minimal real-time computation when new requests arrive, thereby achieving fast response speeds without excessive computational complexity during critical real-time decision-making.
Solution Approach 2:
The system applies segmentation by dividing the transportation planning process into distinct phases: request collection phase, provisional plan creation phase, and real-time execution phase. Each phase handles specific computational tasks independently. The complex optimization algorithms are concentrated in the offline provisional plan creation phase, while the real-time phase only requires simple matching and notification operations. This segmentation isolates computational complexity to non-critical phases, enabling fast real-time response.
Data Source
AI summary
An information processing method to be executed by a transportation plan creation server includes acquiring, from a terminal of each of a plurality of customers who desires to be transported by a vehicle, a transportation request including customer identification information, a boarding date/time, a boarding location, and a disembark location, periodically creating, on the basis of the plurality of transportation requests, a provisional transportation plan in which the plurality of customers is allocated to a plurality of vehicles such that a predetermined constraint condition is satisfied, and outputting, at a first confirmation date/time for confirming the provisional transportation plan, travel schedule notification information for notifying a terminal of the customer allocated to the provisional transportation plan of a travel schedule from boarding to disembarking of the customer allocated to the provisional transportation plan.