Keywords: fuzzy sets, signed distance, fuzzy total cost, lot-sizing, flexibility, centroid, product variety
Received October 14, 2004; revised June 9 & September 28, 2005; accepted October 19, 2005.
Communicated by Chin-Teng Lin.
| Previous | [ 1] | [ 2] | [ 3] | [ 4] | [ 5] | [ 6] | [ 7] | [ 8] | [ 9] | [ 10] | [ 11] | [ 12] | [ 13] | [ 14] | [ 15] | [ 16] | [ 17] | [ 18] | [ 19] | [ 20] |
¡@
Jing-Shing Yao, Wen-Tao Huang* and Tien-Tsai Huang*+
Department of Mathematics
National Taiwan University
Taipei, 106 Taiwan
*Graduate Institute of Management Sciences
Tamkang University
Tamsui, 251 Taiwan
+Department of Industrial Management
Lunghwa University of Science and Technology
Taoyuan, 333 Taiwan
E-mail: normanbb@mail.lhu.edu.tw
In terms of flexibility and product variety in lot-sizing systems of crisp cases, the
average demand of per unit of time (mj), the relative duration of setup (qj), and the unit
cost of production (cj) are considered. Instead of using the usual method that the mj, qj,
and cj in the total cost function are respectively fuzzified by the triangular fuzzy numbers
to derive fuzzy total cost, in this paper, we construct three different intervals to include
mj, qj, and cj, respectively, and then consider the fuzzification of the system from these
three different intervals directly. And finally the fuzzy total cost is obtained. By applying
respectively the signed distance and centroid method for defuzzification, two different
total cost functions are obtained, and thus the respective optimal solutions are computed.
Received October 14, 2004; revised June 9 & September 28, 2005; accepted October 19, 2005.
Communicated by Chin-Teng Lin.