Bi-objective cell loading problem with non-zero setup times with fuzzy aspiration levels in labour intensive manufacturing cells


Sueer G. A. , Arikan F. , Babayigit C.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, cilt.46, sa.2, ss.371-404, 2008 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 46 Konu: 2
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1080/00207540601138460
  • Dergi Adı: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
  • Sayfa Sayıları: ss.371-404

Özet

In this study, four different bi-objective mathematical models are presented to solve the cell loading problem with setup times in labour-intensive cellular environments. The objectives of each model are minimizing the number of the tardy jobs and the minimizing the total manpower needed. Model I does the following four tasks simultaneously: (1) determine the number of cells to open; (2) determine cell size among alternatives for each opened cell; (3) assign products to cells (cell loading); (4) determine the sequence of products in each cell. The other three models are extensions of model I. Model II restricts all cells to the common cell size. Model III allows lot-splitting and model IV allows lot-splitting only if the entire job can be completed. Fuzziness stems from the fuzzy aspiration levels attained to both objective functions. Fuzzy mathematical models are developed for each crisp model and fuzzy achievement function is defined by different fuzzy operators. Experimentation is conducted in two stages. In the first stage, an example problem is solved to represent the performance of the min-operator, fuzzy and- operator and the proposed representation for the fuzzy mathematical modelling. In the second stage, another example is considered to compare the models and to investigate the behaviour of each model with different setup time levels. First, models are solved to maximize the number of the early jobs considering each possible manpower level as a constraint and then fuzzy model solutions are obtained. Experimentation shows that each model represents alternative cell loading systems requirements effectively and the fuzzy and-operator and the proposed fuzzy model representations are convenient to reach the efficient solutions for each model with non-zero setup times.