An integrated multiobjective decision making process for supplier selection and order allocation

Demirtas E., Ustun O.

OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, cilt.36, sa.1, ss.76-90, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 1
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1016/j.omega.2005.11.003
  • Dergi Adı: OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.76-90
  • Anahtar Kelimeler: ANP, MOMILP, interactive, multi-criteria decision making, supplier selection and order allocation, REFERENCE POINT APPROACH, VENDOR SELECTION, SUPPORT-SYSTEM, MULTIPLE, INTEGER, ALGORITHM
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

Supplier selection is a multi-criteria problem which includes both tangible and intangible factors. In these problems if suppliers have capacity or other different constraints two problems will exist: which suppliers are the best and how much should be purchased from each selected supplier? In this paper an integrated approach of analytic network process (ANP) and multi-objective mixed integer linear programming (MOMILP) is proposed to consider both tangible and intangible factors in choosing the best suppliers and define the optimum quantities among selected suppliers to maximize the total value of purchasing and minimize the budget and defect rate. The priorities are calculated for each supplier by using ANP. Four different plastic molding firms working with a refrigerator plant are evaluated according to 14 criteria that are involved in the four clusters: benefits, opportunities, costs and risks (BOCR). Also the priorities of suppliers will be used as the parameters of the first objective function. This multi-objective real-life problem was solved by using e-constraint method and a reservation level driven Tchebycheff procedure. Finally, the most preferred nondominated solutions were determined by considering decision maker's (DM) preferences and the results obtained by these techniques are compared. (c) 2006 Elsevier Ltd. All rights reserved.