I wouldn't be surprised if I've posted in the wrong section because in fact the reason for posting is to get help naming this problem. That being the first step to knowing where to look for a solution. Newbie to the forum so open to advice. The problem: I have a complex histogram and a database of 600 or so less complex histograms. I know all the 'ingredients' (less complex histograms) I need to recreate the complex one are in my database. Some histograms in my db have unique X/Y data pairs ('bars') so definitely belong in my 'reconstructed' histogram the other bars or X/Y data pairs will have to be recreated by summing various 'ingredients' from my database. I need to iteratively sum histograms from my database until I can as closely as possible recreate the original histogram. What class of problem is this? Real world application: I have a perfume, I want to recreate it. In the laboratory I acquire a spectrum (wavelength vs. Intensity; chemical shift vs. Intensity or m/z vs intensity etc - basically x/y data points or histograms) of the perfume. In my database I have spectra (histograms) of Sandlewood Extract, Vanilla, Jasmine, Patchouli, Neroli etc etc. I want to sum the Vanilla, Jasmin etc 'histograms' in various combinations/iterations until I've recreated the original perfume histogram. NB: The Vanilla, Jasmine and other 'ingredient' histograms will have multiple 'peaks' or 'bars', say a dozen, which cannot vary in relative intensity (y-axis), those (relative) values are fixed. Lemon oil and orange oil will have some x axis values that overlap so will sum the intensity (y value) for that x value if both are used in final solution. The final solution is a histograms with 100's of peaks. I don't even know where to begin looking for a solution as I don't know what the problem is called. The best tags I could come up with were 'iterative' and 'optimization'.