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Incorporating genetic algorithm into simulated annealing based redistricting

Redistricting is a process of drawing lines as a boundary, it plays an important role in the process of decision making on space and spatial allocation. In redistricting, the main problem to be solved is to find the districting plan that maximizes the value function involved. Thus, redistricting pro...

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Main Author: Sim, Kwan Hua.
Format: Thesis
Language:English
English
Published: Faculty of Computer Science and Information Technology 2002
Subjects:
QA Mathematics
Online Access:http://ir.unimas.my/id/eprint/500/8/Sim%20Kwan%20Hua%20%2824%20pgs%29.pdf
http://ir.unimas.my/id/eprint/500/10/Sim%20KH.pdf
http://ir.unimas.my/id/eprint/500/
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spelling my.unimas.ir.5002023-08-15T02:09:27Z http://ir.unimas.my/id/eprint/500/ Incorporating genetic algorithm into simulated annealing based redistricting Sim, Kwan Hua. QA Mathematics Redistricting is a process of drawing lines as a boundary, it plays an important role in the process of decision making on space and spatial allocation. In redistricting, the main problem to be solved is to find the districting plan that maximizes the value function involved. Thus, redistricting process can be characterized as a combinatorial optimization problem and considered to be computationally intractable or NP-hard problem, so getting trapped in local optimal and difficulty in obtaining the most optimal solution have became the great challenge of redistricting problem. Latest approach of solving redistricting problem using simulated annealing has shown a significant improvement with ability to escape from local optimal. Faculty of Computer Science and Information Technology 2002 Thesis NonPeerReviewed text en http://ir.unimas.my/id/eprint/500/8/Sim%20Kwan%20Hua%20%2824%20pgs%29.pdf text en http://ir.unimas.my/id/eprint/500/10/Sim%20KH.pdf Sim, Kwan Hua. (2002) Incorporating genetic algorithm into simulated annealing based redistricting. Masters thesis, Universiti Malaysia Sarawak (UNIMAS).
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
English
topic QA Mathematics
spellingShingle QA Mathematics
Sim, Kwan Hua.
Incorporating genetic algorithm into simulated annealing based redistricting
description Redistricting is a process of drawing lines as a boundary, it plays an important role in the process of decision making on space and spatial allocation. In redistricting, the main problem to be solved is to find the districting plan that maximizes the value function involved. Thus, redistricting process can be characterized as a combinatorial optimization problem and considered to be computationally intractable or NP-hard problem, so getting trapped in local optimal and difficulty in obtaining the most optimal solution have became the great challenge of redistricting problem. Latest approach of solving redistricting problem using simulated annealing has shown a significant improvement with ability to escape from local optimal.
format Thesis
author Sim, Kwan Hua.
author_facet Sim, Kwan Hua.
author_sort Sim, Kwan Hua.
title Incorporating genetic algorithm into simulated annealing based redistricting
title_short Incorporating genetic algorithm into simulated annealing based redistricting
title_full Incorporating genetic algorithm into simulated annealing based redistricting
title_fullStr Incorporating genetic algorithm into simulated annealing based redistricting
title_full_unstemmed Incorporating genetic algorithm into simulated annealing based redistricting
title_sort incorporating genetic algorithm into simulated annealing based redistricting
publisher Faculty of Computer Science and Information Technology
publishDate 2002
url http://ir.unimas.my/id/eprint/500/8/Sim%20Kwan%20Hua%20%2824%20pgs%29.pdf
http://ir.unimas.my/id/eprint/500/10/Sim%20KH.pdf
http://ir.unimas.my/id/eprint/500/
_version_ 1775627157144338432
score 13.211869

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