A fuzzy multi-criteria decision-making approach for managing performance and risk in integrated procurement–production planning

Abstract

Nowadays in Supply Chain (SC) networks, a high level of risk comes from SC partners. An effective risk management process becomes as a consequence mandatory, especially at the tactical planning level. The aim of this article is to present a risk-oriented integrated procurement-production approach for tactical planning in a multi-echelon SC network involving multiple suppliers, multiple parallel manufacturing plants, multiple subcontractors and several customers. An originality of the work is to combine an analytical model allowing to build feasible scenarios and a multi-criteria approach for assessing these scenarios. The literature has mainly addressed the problem through cost or profit-based optimisation and seldom considers more qualitative yet important criteria linked to risk, like trust in the supplier, flexibility or resilience. Unlike the traditional approaches, we present a method evaluating each possible supply scenario through performance-based and risk-based decision criteria, involving both qualitative and quantitative factors, in order to clearly separate the performance of a scenario and the risk taken if it is adopted. Since the decision-maker often cannot provide crisp values for some critical data, fuzzy sets theory is suggested in order to model vague information based on subjective expertise. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution is used to determine both the performance and risk measures correlated to each possible tactical plan. The applicability and tractability of the proposed approach is shown on an illustrative example and a sensitivity analysis is performed to investigate the influence of criteria weights on the selection of the procurement-production plan.

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

“…This reflects a general confusion in the literature in defining resilience and other properties characterizing systems affected by threats such as reliability, agility, safety, security, and sustainability, among others (Galaitsi et al 2020). Of the authors that do offer an explicit definition of supply chain resilience, many revert to the definition provided by Ponomarov and Holcomb (2009) of supply chain resilience as the "adaptive capability of the supply chain to prepare for unexpected events, respond to disruptions, and recover from them by maintaining continuity of operations at the desired level of connectedness and control over structure and function" (Gabler et al 2017;Khemiri et al 2017;Yang et al 2017;Valipour Parkouhi and Safaei Ghadikolaei 2017). A number of other authors frame their research around the proactive and reactive components and strategies of resilience (Cheng and et al 2018).…”

Hybrid BWM-ELECTRE-based decision framework for effective offshore outsourcing adoption: a case study

“…According to Ishizaka and Nemery (2014), "It is extremely critical to choose the appropriate MCDM approach applicable for a specific problem". Each MCDM approach has its own uniqueness and applicability which provides flexibility to researchers for making decisions on industry problems (Khemiri et al 2017 (López and Ishizaka 2017). Hence, for the present study ELECTRE is employed to rank the alternatives and compute their adoption index.…”

“…BWM helps to tackle the above discussed issues and provides systematic weight assessment procedures(Rezaei, Hemmes, and Tavasszy 2016).So, for the present study BWM is adopted for computation of enabler weights.The second level in MCDM approaches includes ranking and prioritisation of alternatives.For this purpose, several outranking methods such Complex Proportional Assessment (COPRAS), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Evaluation of Mixed Data (EVAMIX), PROMETHEE, ELECTRE etc. are reported in literature(Khemiri et al 2017). Each method possesses its own credibility and applicability(Yadav, Seth, and Desai 2017).…”

A Group Decision-Making Model for Wastewater Treatment Plans Selection Based on Intuitionistic Fuzzy Sets

“…The general decision-making method cannot be a more realistic reflection of the plan᾽s uncertainties. An intuitionistic fuzzy set offers a better way to deal with uncertain multi-attribute problems (Mehlawat & Grover, 2018;Rodríguez, Ortega, & Concepción, 2017;Ren, Xu, & Wang, 2017;Khemiri, Elbedouimaktouf, Grabot, & Zouari, 2017;Ye, 2017). Thus, the study introduces the intuitionistic fuzzy set to select a wastewater treatment plans.…”