- A Divide and Conquer
- B Trial and Error
- C Backtracking
- D Randomization
Problem-solving strategies - Quiz
- A Divide and Conquer
- B Trial and Error
- C Heuristic
- D Algorithmic
- A Backtracking
- B Heuristic
- C Randomization
- D Greedy Algorithm
- A Divide and Conquer
- B Heuristic
- C Trial and Error
- D Dynamic Programming
- A Strengths, Weaknesses, Opportunities, Threats
- B Sequential, Workflow, Optimization, Task
- C Systematic, Weighted, Objective, Timeline
- D Solution, Workable, Outcome, Tactic
- A Greedy Algorithm
- B Dynamic Programming
- C Randomization
- D Divide and Conquer
- A Divide and Conquer
- B Backtracking
- C Dynamic Programming
- D Trial and Error
- A Synthesis
- B Analysis
- C Divergent Thinking
- D Convergent Thinking
- A Identifying the fundamental cause of a problem
- B Analyzing the external factors influencing a problem
- C Exploring potential solutions to a problem
- D Evaluating the consequences of a problem
- A Heuristic
- B Randomization
- C Greedy Algorithm
- D Backtracking
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Problem-solving strategies - Quiz
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- A. Divide and Conquer
- B. Trial and Error
- C. Backtracking
- D. Randomization
Remarks:
Explanation:
Divide and Conquer is a problem-solving strategy that involves breaking down a complex problem into smaller, more manageable subproblems. Each subproblem is solved independently, and the solutions are combined to address the overall problem.
- A. Divide and Conquer
- B. Trial and Error
- C. Heuristic
- D. Algorithmic
Remarks:
Explanation:
Trial and Error is a problem-solving approach where possible solutions are generated and systematically tested until the correct one is found. It is often used when the solution space is not well-defined or when the problem lacks a known algorithmic solution.
- A. Backtracking
- B. Heuristic
- C. Randomization
- D. Greedy Algorithm
Remarks:
Explanation:
Backtracking is a problem-solving strategy that involves exploring different paths and undoing steps if they lead to undesirable outcomes. It is commonly used in problems where a sequence of decisions needs to be made.
- A. Divide and Conquer
- B. Heuristic
- C. Trial and Error
- D. Dynamic Programming
Remarks:
Explanation:
Heuristic is a problem-solving approach that involves using experience-based techniques to find approximate solutions when an exact solution is impractical or computationally expensive. It relies on rules of thumb or intuition.
- A. Strengths, Weaknesses, Opportunities, Threats
- B. Sequential, Workflow, Optimization, Task
- C. Systematic, Weighted, Objective, Timeline
- D. Solution, Workable, Outcome, Tactic
Remarks:
Explanation:
SWOT stands for Strengths, Weaknesses, Opportunities, Threats. It is a strategic planning tool used in problem-solving to identify internal and external factors that may impact the success of a solution or decision.
- A. Greedy Algorithm
- B. Dynamic Programming
- C. Randomization
- D. Divide and Conquer
Remarks:
Explanation:
A Greedy Algorithm is a problem-solving strategy that involves making the locally optimal choice at each stage with the hope of finding a global optimum. It does not reconsider previous choices once they are made.
- A. Divide and Conquer
- B. Backtracking
- C. Dynamic Programming
- D. Trial and Error
Remarks:
Explanation:
Dynamic Programming is a problem-solving strategy that involves solving subproblems only once and storing their solutions for future reference. It is particularly useful in optimization problems.
- A. Synthesis
- B. Analysis
- C. Divergent Thinking
- D. Convergent Thinking
Remarks:
Explanation:
Synthesis is a problem-solving technique that involves considering multiple solutions to a problem simultaneously and combining their features to create a more optimal solution. It encourages creative thinking and innovation.
- A. Identifying the fundamental cause of a problem
- B. Analyzing the external factors influencing a problem
- C. Exploring potential solutions to a problem
- D. Evaluating the consequences of a problem
Remarks:
Explanation:
Root Cause Analysis refers to the process of identifying the fundamental cause or causes of a problem. It aims to address the underlying issues rather than just the symptoms.
- A. Heuristic
- B. Randomization
- C. Greedy Algorithm
- D. Backtracking
Remarks:
Explanation:
Randomization is a problem-solving strategy that involves using randomness or probability to find a solution, especially when the solution space is vast or undefined. It introduces randomness into the decision-making process.