Final answer:
When choosing an algorithm to solve a problem, trade-offs between time complexity and space complexity are important, while irrelevant factors like the color of the algorithm's flowchart or the name of its creator are not. Roadblocks in problem solving include cognitive biases and lack of information.
Step-by-step explanation:
An algorithm is a set of well-defined instructions for carrying out a particular task and solving problems, often with the same outcome for the same input. In contrast, a heuristic is a general approach or rule of thumb that can be applied to problem-solving but does not guarantee a perfect or even correct solution every time. When choosing an algorithm, there often are trade-offs such as time complexity (how long an algorithm takes to run) versus space complexity (how much memory an algorithm uses). Two factors that are not important trade-offs when selecting an algorithm are the color of the algorithm's flowchart and the name of the algorithm's creator; these factors do not affect the algorithm's performance.
Effective problem solving and decision making can encounter roadblocks such as lack of relevant information, cognitive biases, over-reliance on past solutions that may not fit the current problem, and misunderstanding the real issue at hand. Understanding trade-offs involved in the choice of mathematical models, systems or algorithms is crucial for solving problems effectively, whether in a physics context or in computer science.