Integrated Container Management System Optimizing Logistics
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Solution Overview
Problem
Current container management systems fail to coordinate the transportation of empty containers with customer pick-up and return operations, leading to inefficient movement and imbalance in supply and demand across locations, resulting in increased operational costs.
Innovation Solution
An integrated container management system that simultaneously considers empty container repositioning, pick-up, and return operations, using a network flow solver to optimize container movement and balance supply and demand across depots, while minimizing costs through the integration of booking, forecasting, and cost calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If empty container transportation and customer pick-up/return operations are performed as individual tasks sequentially, then each sub-problem can be addressed individually, but there is no coordination between them resulting in inefficient container movement and increased operational costs
Solution Approach 1:
The patent combines empty container repositioning, pick-up operations, and return operations into a single integrated optimization model. This merging allows the system to consider all operations simultaneously and coordinate them globally, eliminating the inefficiencies caused by sequential independent processing and reducing overall operational costs.
Solution Approach 2:
The integrated management system performs multiple functions simultaneously: it manages empty container repositioning, customer pick-up assignments, and return operations all within one unified platform. This multi-functionality enables coordinated decision-making that optimizes overall container utilization while minimizing operational costs.
2Reliability
If empty container is moved from location B to location A to fulfill customer A's request, then customer A's demand is met, but this movement may be inefficient if a container was already available at location A from customer B's return
Solution Approach 1:
The system performs preliminary analysis by forecasting customer pick-up and return patterns in advance. This allows the system to anticipate that customer B will return a container to location A, and therefore delays or cancels the unnecessary repositioning of another container from location B, saving time and resources while still ensuring demand fulfillment.
Solution Approach 2:
The integrated optimization model continuously monitors and coordinates information between repositioning operations and customer pick-up/return operations. This feedback mechanism allows the system to adjust decisions in real-time, preventing inefficient container movements by using information about upcoming returns to optimize repositioning schedules.
Data Source
AI summary
An input corresponding to a time window is received in an integrated container management system. For containers of a specific container type, a network flow solver implementing a multi-commodity network flow problem is executed based on the input. A graph is generated with nodes representing depot locations, mode of transport locations and customer locations. Arcs connecting nodes, and representing operations and costs associated with the nodes are generated. Pick-up arcs are generated between the depot locations and customer locations. Return arcs are generated between the customer locations and the depot locations. Street turn arcs are generated among customer locations. Unload load arcs are generated between the mode of transport locations and the depot locations. Output tables are generated with values representing functionalities associated with container repositioning, container pick-up and return, and container street turn. Container repositioning, container pick-up and return, and container street turn are optimized based on the values in the output table.