Your general algorithm for problem solving.

Everyone encounters problems in life, ranging from minor inconveniences to major challenges. But how do we tackle these complex issues effectively? In this article, I'll outline a general algorithm in pseudo-code language to help guide you through problem-solving process.

Firstly, let's establish a few introductory axioms to better understand the concept: 

1. Probably every problem is solvable. It's only a matter of how much time and resources you need to finaly solve it.

2. Problems won't solve themselves; action is required. Without action, problems persist. 

3. Having a plan is always better than not having one. A good plan is often integral part of success!

Now, let's look into actual algorithm

---

-- Problem definition stage
define $PROBLEM 
define $DESIRABLE_FINAL_STATE with $MINIMAL_REQUIREMENTS

-- Brainstorm stage
create possible $SOLUTIONS_LIST  
 
do RESEARCH  
  include ASKING_PEOPLE  
  include SEARCH of SIMILAR_PROBLEMS AND THEIR SOLUTIONS in history
  include BRAINSTORMING  
  add $POSSIBLE_SOLUTION to $SOLUTIONS_LIST  
until $SOLUTIONS_LIST is not BIG ENOUGH  
 
order $SOLUTIONS_LIST from the most desirable/probable solution to the least desirable
AND LIMIT your SOLUTION list to TOP N points given time and resources.

-- Execution stage
set $MINIMUM_N_POINTS from the $SOLUTIONS_LIST 
-- MININUM_N_POINTS should be completed to satisfy your minimal requirements.

select $POSSIBLE_SOLUTION from $SOLUTIONS_LIST  then do:
   implement $POSSIBLE_SOLUTION with no hesitating or thinking 
   if implemetation($POSSIBLE_SOLUTION) is successful
   then $COMPLETED_POINTS = $COMPLETED_POINTS + 1 
   else analize('why solution was not successful?')  
 till $COMPLETED_POINTS < $MINIMUM_N_POINTS

---

---

Some concepts (like how big is BIG ENOUGH) are pretty vague, but it's your role to make it more specific as it may be slightly different for each use-case or person.

Note: The SOLUTIONS_LIST contains all points that bring you closer to the desirable final state. Some points may be complementary, other represent alternative solutions. It's your role to order and drop them accordingly during ORDER/LIMIT stage. The SOLUTIONS_LIST may contain varying levels of specificity, ranging from general solutions to highly specific ones. While specificity is preferred, it's not always necessary to be overly detailed. Make sure you're not stepping into analysis paralisis and thin about Occam's razor and Pareto principles.

Here are some scenarios where this algorithm can be applied (this can be anything): 

• Unemployment: Seeking a job at a prestigious company with a desired salary. 
• Time Management: Wanting to accomplish more tasks within a day. 
• Stress Management: Striving for a stress-free lifestyle. 
• Physical Fitness: Working towards a desired body shape. 

Remember these important notes: 

Note 1: Carefully consider whether the problem truly exists before diving into solutions. Many perceived problems are merely products of our imagination and can be addressed through mindset shifts.

Note 2: Delegate tasks when possible. You can't solve every problem yourself. Evaluate whether someone else can handle the task more efficiently. 

Note 3: Once you've committed to problem-solving, avoid hesitation. Overthinking drains motivation and energy. Devote time for refinement and implementation, but don't mix those two together

I've personally applied this algorithm numerous times with success. Do you think it can work for you too? Share your thoughts in the comments!