TY - CHAP
T1 - Modeling supplier selection using multi-criterion fuzzy grouping genetic algorithm
AU - Mutingi, Michael
AU - Mbohwa, Charles
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2017.
PY - 2017
Y1 - 2017
N2 - Supplier evaluation and selection are a complex problem characterized by fuzzy conflicting decision criteria, and imprecise management goals and aspirations. It was realized in this chapter that a number of conflicting criteria may have to be optimized simultaneously if the solution is to be satisfactory. Some of the criteria that were noted are price, lead time, quality, and number of suppliers or vendors selected. Based on an example of subcontractor selection, this chapter presented the supplier selection problem as a grouping problem where groups of tasks (items) can be assigned to each subcontractor, but at a specific cost. It was noted that in the subcontractor selection problem, the tasks may have due dates and precedence constraints, which make the problem even more complicated. This calls for advanced efficient, flexible, and interactive decision support systems that can handle fuzzy variables. To effectively address the fuzzy properties of the problem, a fuzzy multi-criterion grouping genetic algorithm was proposed to model the subcontractor selection. The algorithm uses a fuzzy evaluation approach to convert management goals and aspirations into normalized fuzzy membership functions. Further applications of this model can be applied to similar supplier evaluation and selection problems characterized with (i) multiple suppliers and multiple commodities, (ii) multiple and often conflicting imprecise decision criteria, and (iii) due date restrictions, and/or precedence constraints.
AB - Supplier evaluation and selection are a complex problem characterized by fuzzy conflicting decision criteria, and imprecise management goals and aspirations. It was realized in this chapter that a number of conflicting criteria may have to be optimized simultaneously if the solution is to be satisfactory. Some of the criteria that were noted are price, lead time, quality, and number of suppliers or vendors selected. Based on an example of subcontractor selection, this chapter presented the supplier selection problem as a grouping problem where groups of tasks (items) can be assigned to each subcontractor, but at a specific cost. It was noted that in the subcontractor selection problem, the tasks may have due dates and precedence constraints, which make the problem even more complicated. This calls for advanced efficient, flexible, and interactive decision support systems that can handle fuzzy variables. To effectively address the fuzzy properties of the problem, a fuzzy multi-criterion grouping genetic algorithm was proposed to model the subcontractor selection. The algorithm uses a fuzzy evaluation approach to convert management goals and aspirations into normalized fuzzy membership functions. Further applications of this model can be applied to similar supplier evaluation and selection problems characterized with (i) multiple suppliers and multiple commodities, (ii) multiple and often conflicting imprecise decision criteria, and (iii) due date restrictions, and/or precedence constraints.
UR - http://www.scopus.com/inward/record.url?scp=84990973682&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-44394-2_12
DO - 10.1007/978-3-319-44394-2_12
M3 - Chapter
AN - SCOPUS:84990973682
T3 - Studies in Computational Intelligence
SP - 213
EP - 228
BT - Studies in Computational Intelligence
PB - Springer Verlag
ER -