Multi-criteria evaluation model: an application of MRP parameterization
DOI:
https://doi.org/10.18100/ijamec.817719Keywords:
Multi-Criteria Decision Analysis (MCDA), Optimization, Learning, Decision Support, ParameterizationAbstract
This paper presents a multi-criteria evaluation model applied to the parameterization of the MRP method. Existing optimization approaches that address this problem tend to adopt a means of simulation. A simulated solution is characterized by a pair (parameters, performance indicators). In the context of the evaluation of solutions, the work of Barth, Damand et al. (2003) propose a heuristic approach to extracting knowledge from a solution set. The approach is based on the definition of a multi-criteria solution comparison function. The objective of this paper is to present the detailed modeling of this comparison function. Ultimately, this result contributes to the formalization of a multicriteria optimization problem. A problem solving strategy is proposed.Downloads
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