boost::multi_index_container with random_access and ordered_unique

I have a problem getting boost::multi_index_container work with random-access and with orderd_unique at the same time. (I'm sorry for the lengthly question, but I think I should use an example..)

Here an example: Suppose I want to produce N objects in a factory and for each object I have a demand to fulfill (this demand is known at creation of the multi-index). Well, within my algorithm I get intermediate results, which I store in the following class:

class intermediate_resu开发者_StackOverflowlt
{
private:
    std::vector<int>   parts;     // which parts are produced
    int                used_time; // how long did it take to produce

    ValueType          max_value; // how much is it worth
};

The vector parts descibes, which objects are produced (its length is N and it is lexicographically smaller then my coresp demand-vector!) - for each such vector I know the used_time as well. Additionally I get a value for this vector of produced objects.

I got another constraint so that I can't produce every object - my algorithm needs to store several intermediate_result-objects in a data-structure. And here boost::multi_index_container is used, because the pair of parts and used_time describes a unique intermediate_result (and it should be unique in my data-structure) but the max_value is another index I'll have to consider, because my algorithm always needs the intermediate_result with the highest max_value.

So I tried to use boost::multi_index_container with ordered_unique<> for my "parts&used_time-pair" and ordered_non_unique<> for my max_value (different intermediate_result-objects may have the same value).

The problem is: the predicate, which is needed to decide which "parts&used_time-pair" is smaller, uses std::lexicographical_compare on my parts-vector and hence is very slow for many intermediate_result-objects. But there would be a solution: my demand for each object isn't that high, therefore I could store on each possible parts-vector the intermediate results uniquely by its used_time.

For example: if I have a demand-vector ( 2 , 3 , 1) then I need a data-structure which stores (2+1)*(3+1)*(1+1)=24 possible parts-vectors and on each such entry the different used_times, which have to be unique! (storing the smallest time is insufficient - for example: if my additional constraint is: to meet a given time exactly for production)

But how do I combine a random_access<>-index with an ordered_unique<>-index?

(Example11 didn't help me on this one..)

To use two indices you could write the following:

indexed_by<
  random_access< >,      
  ordered_unique< 
    composite_key< 
      intermediate_result,
      member<intermediate_result, int, &intermediate_result::used_time>,
      member<intermediate_result, std::vector<int>, &intermediate_result::parts>
    >
  >
>

You could use composite_key for comparing used_time at first and vector only if necessary. Besides that, keep in mind that you could use member function as index.

(I had to use an own answer to write code-blocks - sorry!)

The composite_key with used_time and parts (as Kirill V. Lyadvinsky suggested) is basically what I've already implemented. I want to get rid of the lexicographical compare of the parts-vector.

Suppose I've stored the needed_demand somehow then I could write a simple function, which returns the correct index within a random-access data-structure like that:

int get_index(intermediate_result &input_result) const
{
    int ret_value  = 0;
    int index_part = 1;
    for(int i=0;i<needed_demand.size();++i)
    {
        ret_value  += input_result.get_part(i) * index_part;
        index_part *= (needed_demand.get_part(i) + 1);
    }
}

Obviously this can be implemented more efficiently and this is not the only possible index ordering for the needed demand. But let's suppose this function exists as a member-function of intermediate_result! Is it possible to write something like this to prevent lexicographical_compare ?

indexed_by<
  random_access< >,      
  ordered_unique< 
    composite_key< 
      intermediate_result,
      member<intermediate_result, int, &intermediate_result::used_time>,
      const_mem_fun<intermediate_result,int,&intermediate_result::get_index>
    >
  >
>

If this is possible and I initialized the multi-index with all possible parts-vectors (i.e. in my comment above I would've pushed 24 empty maps in my data-structure), does this find the right entry for a given intermediate_result in constant time (after computing the correct index with get_index) ?
I have to ask this, because I don't quite see, how the random_access<> index is linked with the ordered_unique<> index..

But thank you for your answers so far!!