In my thesis, I'm dealing with SLAP (storage location assignment problem) -- which is finding optimal distribution of products to location slots in a generic warehouse. My aim was to implement multiple evolution algorithms (GA, DE, ABC & PSO) to solve this problematic and do a comparison. Since the mentioned problematic (SLAP) is also combinatoric problem with similar constraints and characteristics as TSP, I did research on TSP problematic solved using these algorithms, and applied it on my problem, e.g. based on those papers: GA/PSO, DE, ABC. These approaches were mapped on my problem and works really well. Now, my supervisor told me to create a mathematical proof of TSP - SLAP problematics equivalence or at least some mathematical mapping, he is not doing research in this field so he cannot help me.
To summarize my problem and why I think it is similar to (nearly same as) TSP:
- In TSP, we need to use all cities in the chromosome (solution in general). In my problem, we need to use all articles in the solution.
- In TSP, we cannot have duplicates (we cannot go through one city more then once). In my problem, we also cannot have duplicates, as it would imply that more products are stored within one location slot.
I did some research and found out both SLAP and TSP are NP-Complete problems. It would be possible to create mathematical proof that my problem is NP-Complete. It is both calculated in polynomical time and some well known NP-Complete problem, such as halting problem can be reduced to this problem. Although I don't think this would help me much.
(Pseudo-)formal description: Let's suppose we have $N$ products, and $M$ location slots, where $M$ >= $N$ (as a input). We need to distribute all products to the locations slots, in a way which decreases customer order processing time the most (i.e. all orders has to be processed ASAP). The objective function is duration of order processing and is evaluated as running a simulation of a warehouse (with given distribution of products to slots). So the output is the best possible allocation of the products to slots, which can be expresses simply as a vector of integers, where position in vector specifies article, and the number on the position specifies location slot (into which the product is placed).
Is there any way I can create a proof that these two problems are equivalent or atleast some mathematical mapping from my problem to TSP? Thank you.
If required, I can provide further data, such as chromosomes encoding in GA, ... (but it didn't seem relevant to the proof from my point of view).