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Article detail · 2018 · article

A multiobjective fleet location problem solved by adaptation of evolutionary algorithms NSGA-II and SMS-EMOA

Journal Pamukkale University Journal of Engineering Sciences
ISSN1300-7009
YÖKSİS OpenAlex Open access · diamond TR Index
Year2018
Citations2OpenAlex
Percentile%2.6
FWCI0.01.00 = world average

Data source split

  • YÖKSİSYÖKSİS article record
  • YÖKSİS venuePamukkale University Journal of Engineering Sciences
  • OpenAlexOpenAlex enrichment (abstract, citations, topics)
  • Semantic Scholarcitation count (not merged with OpenAlex)

Abstract

OpenAlex English

The problem of locating naval platforms in the operation region with the aim of maximizing both total radar coverage and critical radar coverage is solved by using Multiobjective Evolutionary Algorithms (MOEA). Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) and S-Metric Selection Evolutionary Multiobjective Optimization Algorithm (SMS-EMOA) procedures are implemented. Experiments show that evolutionary algorithms provide good and diverse alternatives that are considered to be very close to Pareto-optimal front. The performances of NSGA-II and SMS-EMOA approaches are compared employing the hypervolume indicator technique. The performance of NSGA-II is found better in terms of both convergence and diversity.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

2citationsOpenAlex · cited_by_count (cache / database)

2 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. 2024 Radar placement optimization based on adaptive multi-objective meta-heuristicsCitations 25 · OpenAlex
  2. 2024 Radar placement optimization based on adaptive multi-objective meta-heuristicsCitations 22 · OpenAlex

Authors

1
  1. ERTAN YAKICI ÇANKAYA ÜNİVERSİTESİ 1