Claims:1. A system for selecting atleast one optimal route for shipping the goods from one location to another locations using weighted sum of metrics of all routes in the system, the system comprising:
A computing system connected with all the nodes which can gather data for selection of shipments to be transported; and
a plurality of nearby network hub which are embraced with route selection support protocol transparently communicates these attributes exchanging data, and computes the data to determine the selected route and updates destination point for the shipments.

2. The system of claim 1, wherein the rout selection protocol and the plurality of nearby network of hubs communicate via any communication protocol, the route selection acts as the destination point determining entity.

3. The system of claim 1, wherein the route selection protocol computes the optimal route by deriving metrics by product attributes, shipping attributes, route attributes, network of hubs attributes.

4. The system of claim 1, wherein the route selection protocol collects all the consignments to determine the optimal route for each consignments or group of consignments.

5. The system of claim 1, wherein the route selection protocol selects the optimal route via single hop or multiple hops to reach-out the destination for each of the orders placed in the protocol.

6. The system of claim 1, wherein upon receiving the shipment in the network hub, the computing software can update the new destination location, based on the arrivals on the hub.

7. The system of claim 1, wherein the route selection protocol may run in single node or plurality of nodes for shipments till to reach out to the final destination point.

8. A method of computing the optimal route in the available hubs and delivery locations, the method comprising:
Collecting the attributes automatically, semi-automatically or manually by sensors, computing devices, location assisted devices to feed the information’s to the computing protocol.
Analysing the gathered attributes to check the status of shipment, optimal route if any;
Updates the network of computing nodes about the computed route for each node to compute further selection of routes , Description:In the following detailed description, only certain exemplary embodiments of the present invention have been shown and described, simply by way of illustration. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not restrictive. Like reference numerals designate like elements throughout the specification.

It will be further understood that the terms “comprise” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. In addition, the terms “unit”/“module” described in the specification mean units for processing at least one function and operation, and can be implemented by hardware components or software components, and combinations thereof.

Figure 1 shows a shipping network communication according to one embodiment of the present invention. As shown in FIG. 1, the route selection software running on processor circuitry enclosed in a casing. Although embedded, the circuitry (enclosed in a casing) may have the flexibility of running in distributed computing network or cloud computing network. The computing software may be or may include, but is not limited to, distributed computing, Cloud computing, mobile computing, etc. having the electronic circuit embedded or integrated with a computing software to an exemplary embodiment of the present invention. The software computing device includes a operating system 101, route selection software 102, sensors and interfaces 103, memory 104, processor 105, communication network to interconnect all the nodes 106.

The operating system 101 runs on the hardware platform to perform the computing tasks to select the optimal route, such as but not limited to route selection and may extend to parallel running solution along with other process. The operating system 101 interfaces with computing hardware with application processing software 102 to get desired output to the sensors and interfaces devices 103.

The processing software 102 mainly gets all available route options and goods attribute via internet connectivity 106 or by manual entry through sensors and interfaces 103. The processing software 102 computes route selection by applying the weights for each parameters and selects the optimal route and inform the shipping entity.

The sensors and interfaces 103 send the desired route for each consignment, which are activated when receive a command from the controller 102. In this case, the sensors and interfaces 103 has been used to send the selected route to the user entity.

Figure 2 shows a workflow diagram of the various entities present in the present embodiment. The customer 205 connected with computing device such as computer, laptop, and mobile 206 with internet or offline to order the desired product. The order gets processed either directly by shipping agent 203 or pre-processed by administrator 207 and forwarded to shipping agent 203.
The order gets processed and shipping agent 203 starts the shipping to network delivery locations 204 to reach-out customer 205 locations. The selection of network delivery location 204 is determined by processing software defined in 102. The network delivery location 204 receives the goods from shipping agent by delivery 201. The network delivery location 204 gets the optimal supply route and ships

The present system provides a solution which enables optimal route selection during low volume shipments has to reach-out on-time and cost effective route. This avoids wastage of manpower, timely delivery of goods, cost effectiveness by sending the goods to network delivery locations 204, and providing quality of goods like perishable, non-perishable, and freshness.

Figure 3 shows a flow chart of a method of selecting the optimal route, according to one embodiment of the present invention.

At step 310, the product order is placed and activates the computation. The order 310 carries products attributes 320 such as number of orders, quantity, stock, shipping duration, cost, supplier, resource availability and not limited to metrics that are derivative or additional information’s can be gathered about the shipment, order flow and product.

At step 330, the method analyse the gathered data from step 320 information to calculate the weightage. For example, the step of calculating the weightage accounts the product attributes to find the optimal route.
Rs=(ds ×Ws0)+(ts ×Ws1)+(?Npro ×WNpro)+ (Nsp ×Wsp)+(M"Pow (k)"×WPow(k))+ x0
The selected route Rs is weighted sum of distance ds, travelling time ts, number of items to be shipped Npro, number of hubs available Nsp, manpower availability at hub k, constant weight factor x0.
At step 340, the methods classify the selected route and place the order with vendor. The vendor or supplier can accept, reject or forward the order which is implementation specific. The vendor accepts and updates the attributes about the shipment of goods. This vendor attributes 350, fed to the processing software. The shipment will be ready to be shipped 355, if all the attributes are fed and processed 360.

At step 370, the method collects such information from all the orders from various locations are fed to the destination point selection 375 module. The destination point selection 375, computes all weights derived for various shipments. The selected destination point, will calculate the cut-off time computation 380, for shipping locations. This information passed to the origin checking 385. The purpose of origin checking 385 is to ensure the shipments can start from the location or it has to move to nearby hub where regular products services are enabled. Incase of non available hub, it updates the weight into next available hub 390.

At step 392, the method collects the all other shipments data and selects the maximum capacity shipment that can optimize the weights applied based on the optimization goal or target for the shipment. The step 394 selects the common metrics nodes that can be aggregated and designated as the shipping hub.
At step 396, the common metrics node 394, computes and updates the new shipping address for each shipments. All the shipments will receive their updated destignation398, and this will be keep updating in each of the network connecting nodes.

Further, the present invention could use mainly for shipping route selection, transport and extend to any shipments involved.

While the invention has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications can be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. While the principles of the disclosure have been illustrated in relation to the exemplary embodiments shown herein, the principles of the disclosure are not limited thereto and include any modification, variation or permutation thereof.