A scatter search approach for the minimum sum-of-squares clustering problem

2005 ◽  
Vol 32 (5) ◽  
pp. 1325-1335 ◽  
Author(s):  
Joaquı́n A. Pacheco
Keyword(s):  
Scatter Search ◽  
Sum Of Squares ◽  
Clustering Problem ◽  
Search Approach

A tabu search approach for the minimum sum-of-squares clustering problem

2008 ◽  
Vol 178 (12) ◽  
pp. 2680-2704 ◽  
Author(s):  
Yongguo Liu ◽  
Zhang Yi ◽  
Hong Wu ◽  
Mao Ye ◽  
Kefei Chen
Keyword(s):  
Tabu Search ◽  
Sum Of Squares ◽  
Clustering Problem ◽  
Search Approach

CLUSTERING USING AN IMPROVED HYBRID GENETIC ALGORITHM

2007 ◽  
Vol 16 (06) ◽  
pp. 919-934
Author(s):  
YONGGUO LIU ◽  
XIAORONG PU ◽  
YIDONG SHEN ◽  
ZHANG YI ◽  
XIAOFENG LIAO
Keyword(s):  
Genetic Algorithm ◽  
Clustering Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Sum Of Squares ◽  
Clustering Methods ◽  
Clustering Problem ◽  
Mutation Operation ◽  
Iteration Methods ◽  
Genetic Clustering ◽  
The Individual

In this article, a new genetic clustering algorithm called the Improved Hybrid Genetic Clustering Algorithm (IHGCA) is proposed to deal with the clustering problem under the criterion of minimum sum of squares clustering. In IHGCA, the improvement operation including five local iteration methods is developed to tune the individual and accelerate the convergence speed of the clustering algorithm, and the partition-absorption mutation operation is designed to reassign objects among different clusters. By experimental simulations, its superiority over some known genetic clustering methods is demonstrated.

scholarly journals A Scatter Search Approach for Multiobjective Selective Disassembly Sequence Problem

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xiwang Guo ◽  
Shixin Liu
Keyword(s):  
Multiobjective Optimization ◽  
Scatter Search ◽  
Nsga Ii ◽  
Disassembly Sequence ◽  
Selective Disassembly ◽  
Local Search Strategy ◽  
Search Approach ◽  
Nondominated Sorting ◽  
Disassembly Time

Disassembly sequence has received much attention in recent years. This work proposes a multiobjective optimization of model for selective disassembly sequences and maximizing disassembly profit and minimizing disassembly time. An improved scatter search (ISS) is adapted to solve proposed multiobjective optimization model, which embodies diversification generation of initial solutions, crossover combination operator, the local search strategy to improve the quality of new solutions, and reference set update method. To analyze the effect on the performance of ISS, simulation experiments are conducted on different products. The validity of ISS is verified by comparing the optimization effects of ISS and nondominated sorting genetic algorithm (NSGA-II).

Parallel Scatter Search Approach for the MinMax Regret Location Problem

2018 ◽  
Vol 9 (2) ◽  
pp. 1-17
Author(s):  
Sarah Ibri ◽  
Mohammed EL Amin Cherabrab ◽  
Nasreddine Abdoune
Keyword(s):  
Location Problem ◽  
Search Algorithm ◽  
Discrete Event ◽  
Scatter Search ◽  
Search Time ◽  
Computation Time ◽  
Minmax Regret ◽  
Search Approach ◽  
Two Stages

In this paper we propose an efficient solving method based on a parallel scatter search algorithm that accelerates the search time to solve the minmax regret location problem. The algorithm was applied in the context of emergency management to locate emergency vehicles stations. A discrete event simulator was used to test the quality of the obtained solutions on the operational level. We compared the performance of the algorithm to an existing two stages method, and experiments show the efficiency of the proposed method in terms of quality of solution as well as the gain in computation time that could be obtained by parallelizing the proposed algorithm.

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