Classical and urgencies assignment methods in p-median problems with fuzzy genetic algorithm

M. Jalali Varnamkhasti, Nasruddin Hassan

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

The objective in the p-median problem is to minimize the total demand-weighted distance between facilities and demand points. Two different assignment techniques are considered. These techniques are the classical assignment technique and the assignment through urgencies technique. A fuzzy genetic algorithm, crossover operator and crossover rate are used to compare the behavior and efficiency of these methods. The performances of these techniques are assessed by using the benchmark problems currently available in open literature. It is found that the assignment through urgencies is much superior to the classical assignment method.

Original languageEnglish
Pages (from-to)643-651
Number of pages9
JournalPakistan Journal of Statistics
Volume31
Issue number5
Publication statusPublished - 1 Sep 2015

Fingerprint

P-median Problem
Fuzzy Algorithm
Assignment
Genetic Algorithm
Crossover Operator
Crossover
Benchmark
Minimise

Keywords

  • Fuzzy genetic algorithm
  • P-median problem
  • Sexual selection
  • Urgencies assignment

ASJC Scopus subject areas

  • Statistics and Probability

Cite this

Classical and urgencies assignment methods in p-median problems with fuzzy genetic algorithm. / Varnamkhasti, M. Jalali; Hassan, Nasruddin.

In: Pakistan Journal of Statistics, Vol. 31, No. 5, 01.09.2015, p. 643-651.

Research output: Contribution to journalArticle

Varnamkhasti, M. Jalali ; Hassan, Nasruddin. / Classical and urgencies assignment methods in p-median problems with fuzzy genetic algorithm. In: Pakistan Journal of Statistics. 2015 ; Vol. 31, No. 5. pp. 643-651.
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