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System and Method for Real Time Cold Chain Distribution Optimization

IP.com Disclosure Number: IPCOM000210454D
Publication Date: 2011-Sep-06
Document File: 5 page(s) / 166K

Publishing Venue

The IP.com Prior Art Database

Abstract

Cold chain optimization is attracting more and more attention because of financial pressure and regulatory demands. With the application of Internet of Things technology in cold chain, more and more trucks are equipped with sensors, such as temperature, GPS, RFID, etc. A system and method for real time cold chain distribution optimization is provided using real time sensor data. First, the system components and data flow are provided. Then, an optimization approach is proposed to select the best action for exception situation. A whole truck decision making and item level decision making approach are provided. Finally, the best action is selected.

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System and Method for Real Time Cold Chain Distribution Optimization

Existing cold chain monitoring systems are typically equipped with sensor technology, namely environment sensor (RFID) and GPS module on the truck, to guarantee the freshness of foods during transportation while reducing the cost in real time. How to use these reported temperature sensor and GPS data to optimize the distribution plan and distribution cost is important to satisfy the client, reduce the distribution cost under the guarantee of freshness.

Existing solutions are experience based. They are not optimal and also difficult to achieve real time processing. Meanwhile, they don't consider the freshness of food. To achieve real time cold chain distribution optimization, a system and method for real time cold chain distribution optimization is provided using real time sensor data.

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Figure 1 System components and data flow

The system consists of the following components as shown in Figure 1.

Product temperature calculator. This module is used to calculate the real temperature of each item based on the readings from sensors deployed in the truck. The space interpolation or computational fluid mechanics method can be used to estimate the real temperature of each item.

Freshness calculator. This module is used to calculate the freshness of each item based on historic temperature of this item as shown in Figure 2. The knowledge of relationship between temperature and freshness is required in advance.

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                                   Figure 2 Illustration for freshness calculation
GIS. GIS is used to get the available route and distance information for the optimizer.

Other data sources. Other data sources like the distribution center information, the truck status are necessary for the optimizer. Action optimizer. This component is used to calculate the optimal solution based on the input from the above mentioned components. The model of the optimizer is as follow:

Objective

ta

min

ctaj x

*

T

t A

a J

j

Î Î Î

Subject to

Product quality guarantee Commitment fulfillment Available nearby resources Traffic information

Where:

T : the set of refrigerated trucks

A

  : the set of possible actions J : the set of cost factors

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: cost of factor

j if apply action

a to truck t

There are three types of actions. The description and benefits are shown in Table 1.

Type of actions Description Benefit

Change destination

Change the delivery plan for some of the trucks in company.

For example:
let the problem truck deliver items to a nearby destination that was assigned to another truck
the other trucks deliver the items to the new assigned destination

Using social network help

Some other resources close to this exception truck,...