Fifty-six years ago, a paper appeared in Operations Research (vol 6, p1-10) with the title: "Heuristic Problem Solving: The Next Advance in Operations Research". Written by Herbert A. Simon and Allen Newell, it daringly proposed advances in the power of computers to solve problems by heuristic methods, and not by purely algorithmic methods. It caused a flurry of discussion in the correspondence section of the journal.
Since then, we have become accustomed to the use of heuristic methods as part of the tool-kit of O.R. But we do not have one heuristic method for problem solving - we have many. Some of them have developed into the well-established metaheuristics of simulated annealing, tabu search, genetic algorithms, ant-based algorithms, and many others. A glance at the content pages of our journals, or (even better since it classifies papers) through the index of the International Abstracts in O.R., will show how often heuristics have been used to advantage in the "Science of Better". Of course, heuristics are for finding "better" rather than "optimum", although there are many situations where the heuristics do find an optimum.
But it is salutary to look at the frequency of heuristics in the equipment we use in everyday life. Usually the heuristic is hidden in some computer chip or electronic circuitry, and only by stopping to think about it do we recognise that someone, somewhere, has realised that a heuristic is needed and has programmed it. One of the earliest papers on heuristics that I ever read (and I can't find a reference to it - any suggestions?) gave a list of simple, everyday heuristics. "Use an old golf ball when there is water hazard". "Order a new chequebook when you reach the reminder slip in your present one" and so on. The second of these examples is now outdated with my bank; the bank's computer has a heuristic which recognises when I am nearing the end of the chequebook, and issues a new one without my need to remind the bank. I wonder whether the heuristic also has a parameter based on the average number of cheques that I write each month. So there is a heuristic that affects my life.
What about others? We replaced our old car with a newer model a few months ago. This one has several heuristics built into its control electronics. With the headlights set to an automatic setting, the lights come on when a sensor detects the ambient light levels to be too low. That is wonderful - except that the headlights come on when we drive the car into or out of the garage. They also come on in some Devon lanes, when the hedges or banks create a dark canyon. The heuristic is good, but it isn't optimal. The car has sensors for the drag on the windscreen wipers, so adjusts the sweep if there is light rain. That heuristic can be disconcerting, if, like us, you are used to regular sweeps of the wipers.
The kitchen is another place where everyday life encounters heuristics. The freezer pump switches on when it detects an internal temperature which is too high - but it is not so sensitive that it will switch on immediately the door is opened. The oven has a thermostat which controls the heating elements and fan - according to a simple heuristic. I was surprised to see an advert for an oven which claimed that it could be controlled to an accuracy of one degree Celsius. None of the recipes that I use require such excessive accuracy.
The radio tunes when there is a signal of sufficient strength. The mobile phone operates with numerous heuristics.
So are these heuristics that solve problems part of the breakthrough that Simon and Newell anticipated? Yes. They are parts of the hidden application of O.R. in twenty-first century life. And there are many, many more.