Problem-solving strategies are an essential part of all the possible spheres of life: regular day-to-day life, business, and politics. That is why it is also vital to differentiate various techniques as their advantages can contribute more depending on the situation. Being aware of those differences guarantees an individual and a decision-maker the most productive ways to overcome a challenge. For instance, sometimes even the simplest models, like algorithms, can be more productive than more sophisticated strategies such as heuristics.
Firstly, algorithms can be understood as a scheme of actions or a procedure aimed to solve a problem. Typically, it requires the following step-by-step instructions that are supposed to guarantee the result. Speaking of the real-life examples, once I decided to acquire a bike to increase my physical activity, but I also never wanted to spend a lot of money on anything. So I started to scroll the second-hand’s Internet sites seeking suitable offers, one-by-one. As a result, the search was successful but too time-demanding. Hence, such an algorithm was an effective strategy in my case, because I have no expertise in bikes, so optimizing the process was challenging.
Secondly, there is another problem-solution strategy – heuristics, known as a general framework to overcome issues. In other words, it is an optimization of solutions that, nevertheless, do not guarantee that the strategy is correct. For instance, my best friend likes to write to-do lists in order to boost her work’s effectiveness. Another example that illustrates this strategy is the way my partner and I plan our vacations: we break the task into small steps and share the responsibilities. While one plans the itinerary and buys plane tickets, the other seeks exciting spots in a new place and books a hotel.
As for the situations when algorithms are more effective than the heuristics strategy, one may imagine plenty. On the one hand, the process of coming up with a heuristically planned solution can be more time-consuming, especially when one does not have enough knowledge of the problem they solve. Artificial intelligence today is an excellent example of such a case. On the other hand, due to that lack of expertise, the decision-maker can ignore essential factors that prevent them from solving a problem, according to one’s heuristics. For example, when I came to another city for a conference, I was given directions by the event organizers. Taking a look at the map, I thought a came up with a shorter route. As a result, I was late, as the road works blocked that way, and I had to follow the initially recommended route. Instead of following the instructions or an algorithm, I came up with a heuristics strategy that failed due to my lack of experience living in the area. Therefore, there are multiple real-life scenarios when simple algorithms appear to be significantly more effective than heuristics.
To conclude, a rational choice of a problem-solution model is extremely important in any realm of human activity, even in a personal day-to-day routine. For instance, algorithms are probably the most straightforward strategy an individual may implement: it sometimes appears to be too time-consuming, and some seek more efficient ways. Meanwhile, there is also a strategy of heuristics, which requires more planning and organization that does not guarantee a solution as much as algorithms.