Multiple-criteria decision-making in two-sided assembly line balancing: A goal programming and a fuzzy goal programming models


ÖZCAN U., TOKLU B.

COMPUTERS & OPERATIONS RESEARCH, cilt.36, sa.6, ss.1955-1965, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 6
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.cor.2008.06.009
  • Dergi Adı: COMPUTERS & OPERATIONS RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1955-1965
  • Anahtar Kelimeler: Two-sided assembly line balancing, Pre-emptive goal programming, Fuzzy goal programming, Multiple-criteria decision-making, ALGORITHM
  • Gazi Üniversitesi Adresli: Evet

Özet

Two-sided assembly lines are especially used at the assembly of large-sized products, such as trucks and buses. In this type of a production line, both sides of the line are used in parallel. In practice, it may be necessary to optimize more than one conflicting objectives simultaneously to obtain effective and realistic solutions. This paper presents a mathematical model, a pre-emptive goal programming model for precise goals and a fuzzy goal programming model for imprecise goals for two-sided assembly line balancing. The mathematical model minimizes the number of mated-stations as the primary objective and it minimizes the number of stations as a secondary objective for a given cycle time. The zoning constraints are also considered in this model, and a set of test problems taken from literature is solved. The proposed goal programming models are the first multiple-criteria decision-making approaches for two-sided assembly line balancing problem with multiple objectives. The number of mated-stations, cycle time and the number of tasks assigned per station are considered as goals. An example problem is solved and a computational study is conducted to illustrate the flexibility and the efficiency of the proposed goal programming models. Based on the decision maker's preferences, the proposed models are capable of improving the value of goals. (C) 2008 Elsevier Ltd. All rights reserved.