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Generating and solving difficult logic puzzles with LLMs

2 pointsby frogger84 months ago
make a logic puzzle for restaurant staffing. Have 23 employees and create a situation that is insane level hard to schedule the shifts. &quot;I&quot; will try to figure out an answer and verify with you if &quot;I&quot; am correct<p>The restaurant has 23 employees. The goal is to create a schedule that satisfies all the constraints below. Each shift must be completely staffed, and no rules can be violated.<p>Employees: There are 23 employees with the following specialties:<p>Chefs (C): Alice, Bob, Charlie, David, Evelyn Servers (S): Fiona, George, Hannah, Ian, Julia, Kevin, Lily, Mason, Natalie, Olivia Hosts (H): Peter, Quinn, Rachel, Sam Dishwashers (D): Tim, Ursula, Victor<p>Full details https:&#x2F;&#x2F;chatgpt.com&#x2F;share&#x2F;67772c03-977c-8007-acb0-6881fdabae42<p>Answer generated by claude https:&#x2F;&#x2F;claude.site&#x2F;artifacts&#x2F;ce387d7f-cd9a-4440-9ba1-b4cc366a70bd

3 comments

talldayo4 months ago
This is not what HN is used for. Don&#x27;t create submissions just to report an AI response.
评论 #42580647 未加载
brudgers4 months ago
At first blush, this might be Job Shop Scheduling {1}. But I don&#x27;t know {2}. If so, it is NP-Hard which means verifying an optimal solution is also in NP.<p>An LLM might be able to solve a toy scale problem with only four operations and lots of &quot;machines.&quot; But I am skeptical it can solve problems of &quot;interesting size&quot; more effectively than numerical techniques because verification is also in NP. {3} Good luck.<p>{1} <a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Job_shop_scheduling" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Job_shop_scheduling</a><p>{2} &quot;All shifts covered&quot; seems like a requirement for optimality.<p>{3} Assuming the problem is Job Shop Scheduling.
frogger84 months ago
Note deepseek FAILED to figure it out