Even though many optimizations based on heuristics(I mean ways to increase the tree depth without actualy searching) discussed in chess programming literature, I think most of them are rarely used. The reason is that they are good performance boosters in theory, but not in practice.
Sometimes these heuristics can return a bad(I mean not the best) move too.
The people I have talked to always recommend optimizing the alpha-beta search and implementing iterative deepening into the code rather than trying to add the other heuristics.
The main reason is that computers are increasing in processing power, and research[need citation I suppose] has shown that the programs that use their full CPU time to brute force the alpha-beta tree to the maximum depth have always outrunned the programs that split their time between a certain levels of alpha-beta and then some heuristics,.
Even though using some heuristics to extend the tree depth can cause more harm than good, ther are many performance boosters you can add to the alpha-beta search algorithm.
I am sure that you are aware that for alpha-beta to work exactly as it is intended to work, you should have a move sorting mechanisn(iterative deepening). Iterative deepening can give you about 10% performace boost.
Adding Principal variation search technique to alpha beta may give you an additional 10% boost.
Try the MTD(f) algorithm too. It can also increase the performance of your engine.