Optimal Seating Arrangement Algorithm for Friendship Graphs

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SUMMARY

The discussion centers on developing an algorithm for determining the optimal seating arrangement based on a directed friendship graph formatted in xkcd style. The proposed input consists of two matrices: an nxn matrix representing the strength of relationships among n visitors and an mxm matrix indicating the adjacency of m seats. The output should be a list of m numbers that specify which visitor occupies each seat. The algorithm must evaluate all possible seating arrangements to maximize the overall satisfaction based on the defined relationships.

PREREQUISITES
  • Understanding of directed graphs and their representation
  • Familiarity with matrix operations and data structures
  • Knowledge of algorithm optimization techniques
  • Experience with computational complexity analysis
NEXT STEPS
  • Research algorithms for solving the Traveling Salesman Problem for optimization techniques
  • Learn about graph theory concepts, specifically directed graphs and adjacency matrices
  • Explore dynamic programming approaches for combinatorial optimization
  • Investigate heuristic methods for seating arrangement problems, such as genetic algorithms
USEFUL FOR

This discussion is beneficial for algorithm developers, data scientists, and anyone involved in optimizing seating arrangements based on relational data, particularly in social or event planning contexts.

happinessuni
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Hi all,

I am struggling the question, please see attachments.

Thanks a lot

View attachment 6522View attachment 6523

Devise an algorithm which, given a (directed) friendship graph (in the xkcd format), finds the optimal seating arrangement. Your algorithm should include the following:
 a description of the required input format
 appropriate weightings of the four types of edges in the given friendship graph
 an output (an optimal seating arrangement)
 sufficient explanation of the variables and data structures involved that the marker can tell what they are for.
 

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Hi happinessuni! Welcome to MHB! (Smile)

Hmm... suppose we have n visitors and m seats.
Then the input could for instance be a nxn matrix with numbers indicating the strength of the relationship.
And combined with a mxm matrix indicating which seats are next to each other.
The output could be m numbers indicating which visitor sits on each seat.
Then the algorithm could try all ways that the visitors could be seated, evaluating how 'well' the seating is, and selecting the one with the most value.
If calculation time is an issue, there are several ways to optimize it... (Thinking)

Any thoughts?
 
I like Serena said:
Hi happinessuni! Welcome to MHB! (Smile)

Hmm... suppose we have n visitors and m seats.
Then the input could for instance be a nxn matrix with numbers indicating the strength of the relationship.
And combined with a mxm matrix indicating which seats are next to each other.
The output could be m numbers indicating which visitor sits on each seat.
Then the algorithm could try all ways that the visitors could be seated, evaluating how 'well' the seating is, and selecting the one with the most value.
If calculation time is an issue, there are several ways to optimize it... (Thinking)

Any thoughts?

Hi, Thanks for reply, I still didn't get the algorithm, could you please show me how to find it?
 

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