Title :
An approach based on simulation optimization and AHP to support collaborative design: With an application to supply chains
Author :
Baccouche, Ahlem ; Goren, Selcuk ; Huyet, Anne-Lise ; Pierreval, Henri
Author_Institution :
IFMA, Clermont Univ., Aubiere, France
Abstract :
In certain design problems, the solution can have collective implications that are experienced by a number of different people with different responsibilities - a team of decision-makers. In such cases, the design problem should be addressed in a collective manner, so that everyone´s considerations are taken into account. Unfortunately, even though there is a vast body of literature on simulation optimization, which is widely used to solve the design problems encountered in practice, the existing research generally concentrates on providing a single solution that is optimized according to one or more performance measures. In this paper, we consider the problem of determining the values of several decision variables of a design problem where several decision-makers are involved, who have different preferences for the final solution. The different designers´ considerations may not be all known in advance or may not be included in the simulation model, but can only be examined once a candidate solution is proposed. To cope with such difficulties, we propose a two-stage approach. It is first necessary to find a set of different enough designs that can be considered efficient in terms of performance. The solutions can afterwards be passed on to the decision-makers and the most appropriate one can be decided on according to their preferences. We use the crowding clustering genetic algorithm (CCGA) to solve the first sub-problem, where the performances of the candidate designs are evaluated using simulation. We address the second sub-problem with a multiplicative variant of the popular analytic hierarchy process (AHP), which does not suffer from the dependence on irrelevant alternatives as the original version. We illustrate the benefits of the proposed two-stage approach on a supply chain design problem.
Keywords :
decision making; design; genetic algorithms; pattern clustering; supply chains; AHP; CCGA; analytic hierarchy process; crowding clustering genetic algorithm; decision making; design problem; simulation optimization; supply chain design problem; support collaborative design; Analytical models; Clustering algorithms; Decision making; Genetic algorithms; Optimization; Supply chains; Analytic Hierarchy Process; multimodal optimization; simulation optimization; supply chain;
Conference_Titel :
Computational Intelligence In Production And Logistics Systems (CIPLS), 2011 IEEE Workshop On
Conference_Location :
Paris
Print_ISBN :
978-1-61284-331-5
DOI :
10.1109/CIPLS.2011.5953360