Event Title
Heuristics for the Sudoku Distances Problem
Location
Science Center, Bent Corridor
Start Date
10-28-2016 5:30 PM
End Date
10-28-2016 6:00 PM
Research Program
Research Experience for Undergraduates (REU) program, Department of Mathematics, Statistics and Computer Science, Marquette University
Poster Number
21
Abstract
The Sudoku Distances Problem (or SDP) is a graph theoretic problem which asks for the minimum-weight Hamiltonian path through a complete weighted graph, from a specified start vertex. Edges in SDP instances are weighted according to the "Manhattan distance" between their endpoints. The SDP is a variation of the Traveling Salesman Problem, which holds importance in complexity theory and the whole of computer science. We use graph theoretic methods to analyze general instances of the SDP and their solutions. We show that a solution to an arbitrary instance of the SDP (i.e. a minimum-weight path) never needs to cross itself in its geometric representation, and present a heuristic for the SDP which utilizes that result by avoiding paths which cross themselves. We present another heuristic which takes advantage of the properties of spaces which use "Manhattan distance" as a]their distance metric.
Recommended Citation
Miller, Joel, "Heuristics for the Sudoku Distances Problem" (2016). Celebration of Undergraduate Research. 36.
https://digitalcommons.oberlin.edu/cour/2016/posters/36
Major
Computer Science
Project Mentor(s)
Kim Factor, Math, Statistics, and Computer Science Department, Marquette University
Document Type
Poster
Heuristics for the Sudoku Distances Problem
Science Center, Bent Corridor
The Sudoku Distances Problem (or SDP) is a graph theoretic problem which asks for the minimum-weight Hamiltonian path through a complete weighted graph, from a specified start vertex. Edges in SDP instances are weighted according to the "Manhattan distance" between their endpoints. The SDP is a variation of the Traveling Salesman Problem, which holds importance in complexity theory and the whole of computer science. We use graph theoretic methods to analyze general instances of the SDP and their solutions. We show that a solution to an arbitrary instance of the SDP (i.e. a minimum-weight path) never needs to cross itself in its geometric representation, and present a heuristic for the SDP which utilizes that result by avoiding paths which cross themselves. We present another heuristic which takes advantage of the properties of spaces which use "Manhattan distance" as a]their distance metric.