Heuristic

[Mark Lawrence]

Please stop top posting!!!

On 25/06/2010 15:14, Nathan Rice wrote:
> I solve optimization problems like this all the time using branch and bound.
> Just arrange the possible scenarios into a state space tree, (ideally
> ordered by lowest average cost supplier) then prune any branch where the
> best case scenario given supplier cost plus shipping cost summed over all
> remaining orders is greater than your current best total cost.  You can make
> it pretty fast in python if you implement memoization of supplier
> fulfillment costs for orders.  All you need to do is write a depth first
> search algorithm (stack based, not recursive), a best case predictor for a
> single order fulfillment (which is summed over all unfulfilled orders) and
> an actual cost for order fulfillment function.  It's really easy to put
> together, and tends to work quite well.
>
> On Fri, Jun 25, 2010 at 7:24 AM, Marcos<marcosruapuga at gmail.com>  wrote:
>
>> On 25 jun, 04:00, MRAB<pyt... at mrabarnett.plus.com>  wrote:
>>> Terry Reedy wrote:
>>>> On 6/24/2010 9:13 PM, Marcos wrote:
>>>>> I have a store, so I want to maximize the profit. I have all the
>>>>> suppliers with diferent prices, some providers can send products to a
>>>>> client an others not, this has a plus price. Some providers has a
>>>>> discount over the tansport if a quantity is reached.
>>>
>>>>> Sometimes its better to me receive the order and resend to the client
>>>>> if I have a transport discount.
>>>
>>>>> Not all the suppliers has all products for a order.
>>>
>>>>> So I want to create a function which I can pass the data, and
>>>>> generates all the possibilities so I can find the maximum profit.
>>>
>>>>> Have I to use heuristics? Do you know some examples?.
>>>
>>>> You would not use a heuristic to generate all possibilities. You might
>>>> use one to *avoid* doing that, and still get a good, not necessarily
>>>> optimal, answer.
>>>
>>> True. Basically there are two ways of approaching the problem. One is to
>>> try all the combinations, which will guarantee that you'll find the best
>>> solution, but if there are an enormous number of combinations then that
>>> could take a very long time. The other way is to use a heuristic to get
>>> an reasonable solution in an reasonable time. It's a trade-off.
>>>
>>>   >  Wikipedia has an general entry on 'heuristic'.
>>>   >  Algorithm books often specifically discuss heuristic algorithms.
>>
>> Do you know it there is some way to generate all the scenario
>> possibilities?. So I Can put an array an data an generate all. I have
>> the lack of repeated elements that I cant solve.
>>
>> Thanks.
>> --
>> http://mail.python.org/mailman/listinfo/python-list
>>
>