Goal programming using multiple objective tabu search

Baykasoglu A.

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, cilt.52, sa.12, ss.1359-1369, 2001 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 52 Sayı: 12
  • Basım Tarihi: 2001
  • Doi Numarası: 10.1057/palgrave.jors.2601229
  • Dergi Adı: JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.1359-1369
  • Anahtar Kelimeler: goal programming, multiple objective tabu search, multi-objective optimisation, CONTINUOUS-VARIABLES, OPTIMIZATION, ALGORITHM, DESIGN
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

Goal programming (GP) is one of the most commonly used mathematical programming tools to model multiple objective optimisation (MOO) problems, There are numerous MOO problems of various complexity modelled using GP in the literature, One of the main difficulties in the GP is to solve their mathematical formulations optimally. Due to difficulties imposed by the classical solution techniques there is a trend in the literature to solve mathematical programming formulations including goal programmes, using the modern heuristics optimisation techniques, namely genetic algorithms (GA), tabu search (TS) and simulated annealing (SA). This paper uses the multiple objective tabu search (MOTS) algorithm, which was proposed previously by the author to solve Gl? models. In the proposed approach, GP models are first converted to their classical MOO equivalent by using some simple conversion procedures. Then the problem is solved using the MOTS algorithm. The results obtained from the computational experiment show that MOTS can be considered as a promising candidate tool for solving GP models.