Probabilistic Linguistic VIKOR Method to Evaluate Green Supply Chain Initiatives

2017 
To achieve the goals of sustainable economic and environmental protection, more and more firms intend to implement green supply chain (GSC) initiatives in their products. The adoption of GSC initiatives in turn influences the firms’ operations performance. Thus, the firms have to evaluate their performances carefully when implementing GSC initiatives. The performance evaluation of GSC initiatives is a laborious task, which needs to take into account many factors including the inventory level and assurance of supply purchasing-wise and the technical capability and the innovation capability manufacturing-wise, etc. This paper develops a new probabilistic linguistic VIKOR approach to support such an assessment. To do so, a new comparison method of probabilistic linguistic term sets (PLTSs) is first presented to effectively determine the probabilistic linguistic positive ideal solution and the probabilistic linguistic negative ideal solution. Next, a new defuzzification function of PLTSs is proposed to take into account the main-criteria weights and the sub-criteria weights which are represented by PLTSs. Furthermore, several probabilistic linguistic measures are introduced, such as the probabilistic linguistic group utility measure, the probabilistic linguistic individual regret measure and the probabilistic linguistic compromise measure. Finally, the compromise solution is obtained based on these three measures. The desirable advantages of the developed method are summarized as (1) it allows the evaluators to employ PLTSs to express the imprecise performances of the GSC initiatives with respect to various criteria, which greatly improves the elicitation of linguistic information; (2) it presents a probabilistic linguistic compromise solution, which is a maximum probabilistic linguistic group utility for the majority and a minimum probabilistic linguistic individual regret for the opponent. This proposed technique provides a simple and efficient decision making approach to assist the firms to make an appropriate decision in GSC management.
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