Abstract: Supplier selection, in real situation, is affected by
several qualitative and quantitative factors and is one of the most
important activities of purchasing department. Since at the time of
evaluating suppliers against the criteria or factors, decision makers
(DMS) do not have precise, exact and complete information, supplier
selection becomes more difficult. In this case, Grey theory helps us
to deal with this problem of uncertainty. Here, we apply Technique
for Order Preference by Similarity to Ideal Solution (TOPSIS)
method to evaluate and select the best supplier by using interval
fuzzy numbers. Through this article, we compare TOPSIS with some
other approaches and afterward demonstrate that the concept of
TOPSIS is very important for ranking and selecting right supplier.
Abstract: The objective of this research is to calculate the
optimal inventory lot-sizing for each supplier and minimize the total
inventory cost which includes joint purchase cost of the products,
transaction cost for the suppliers, and holding cost for remaining
inventory. Genetic algorithms (GAs) are applied to the multi-product
and multi-period inventory lot-sizing problems with supplier
selection under storage space. Also a maximum storage space for the
decision maker in each period is considered. The decision maker
needs to determine what products to order in what quantities with
which suppliers in which periods. It is assumed that demand of
multiple products is known over a planning horizon. The problem is
formulated as a mixed integer programming and is solved with the
GAs. The detailed computation results are presented.