on 04-26-2012 3:32 PM
We are using APO 5.1.
We are using SNP heuristics to plan supply between DCs and factories (with transport lanes between factories and DCs) , but we now want to look at stock balancing across DCs.
I think using SNP optimisation is one possible approach using different storage and production costs.
But are there other possible solutions?
Any help is appreciated...
Hello,
Deployment is the best option. You can specify fair share rule B so supply is distributed evenly across locations based in target stock levels. You can also specify quotas at locations using rule C.
Regards,
Steve
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Hi,
I did not clearly understand what your requirement of 'stock balancing' is. This is a very generic term.
May be even Network or Multilevel Heuristics could take care of some sinple requirements depending on your network.
Otherwise Deployment also provide functionalities to deploy the supplies to the demands.
If the network is complex and you want to have a plan considering multiple factors/constraints at the same time, then optimizer is definitely one of the options.
Once you provide some more "specific" information about your requirement, then someone should be able to suggest some solution.
Thanks - Pawan
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Hi, As you mentioned SNP optimization is one option if you have clear goal of what/where and how to optimize. Another factor you should look at is safety stock balancing across network. Where/how much/when should safety stock should be available in the network. Again this depends on the what kind of industry and business processes. Hope this helps. Thanks
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Hi,
Could you please throw some light on stock balancing?
If you are looking for stock balancing from entire network perspective, probably you can check multi-echelon inventory optimization software SMARTOPS (can be integrated with APO).
Otherwise, simple location based stock maintenance, you can define appropriate push distribution (extra supply) or fair share rules (demand exceeds supply) in SNP2 of location product master record. These values are considered in deployment or optimizer run.
Thanks,
Rajesh
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