A novel multiple criteria decision-making approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy AHP for mapping collection and distribution centers in reverse logistics

L.A. Ocampo, C.M. Himang, A. Kumar, M. Brezocnik
2019 Advances in Production Engineering & Management  
chief sustainable practice is the end of life (EOL) strategies which intend to restore goods to its original working condition (USITC, 2012 [6]). Among the extant EOL strategies, the concept of remanufacturing is of growing interest to scholars from domain disciplines (Rashid et al., 2013 [3]). As an industrial process, the goal of remanufacturing is to recover the residual value of used products by reconditioning and reusing components that are still functional and acceptable (Wei et al., 2015
more » ... [7]). It is a product recovery technique (PRT) that promotes sustainability as it helps firms achieve closed-loop supply chains. Remanufacturing addresses the environmental, social, and economic dimensions of sustainability by minimizing waste and emission generation, creating jobs, and trimming down production costs by 50 % (Rathore et al., 2011 [8]; Chen and Chang, 2012 [9]; Xiaoyan, 2012 [10]). Several original equipment manufacturers (OEMs) have taken an interest in remanufacturing such as Caterpillar, HP, Xerox, and Kodak to increase profit and improve their social and environmental performances as well. This increased attention can be attributed to remanufacturing's benefits and essential functions in the ever-changing society. In remanufacturing, one of the crucial aspects is reverse logistics. Reverse logistics is the process of planning, implementing, and controlling efficient, effective inbound flow, inspection, and disposition of returned products and related information for recovering value (Srivastava, 2006 [11]). The collected EOL products are subjected to a detailed inspection, which either ends up remanufactured or disposed. Products that go through the remanufacturing process are distributed in secondary markets; afterward, the cycle of collection and remanufacturing continues. The practice of remanufacturing, however, is rather hindered despite its advantages in terms of sustainability since the receptivity of consumers varies from one region to another, as suggested in the current literature. That is, consumers in well-developed Western countries are more open to remanufactured products compared to those in most developing countries (Nnorom and Osibanjo, 2008 [12]; Zou et al., 2016 [13]). As critical tasks of reverse logistics, several studies in the literature tackled how these functions can be optimized according to collection rate and sales (Malik et al., 2015 [14]; Pop et al., 2015 [15]), profit and return rate (Hong and Yeh, 2012 [16]), and economies of scale (Atasu et al., 2013 [17]), to name a few. Consequently, dominant mathematical models such as continuous modeling frameworks (Wojanowski et al., 2007 [18]), a mixed-integer nonlinear model (Min and Ko, 2008 [19]), and graph theory and matrix approach (Malik et al., 2015 [14]) are adapted to design such functions. While prior studies in literature present mathematical models with single objective analyses to optimize collection and distribution decision problems, these methodologies fail to incorporate various aspects and holistic considerations that are necessary for the decision problem involving the location of centers (Malik et al., 2015 [14]). Real-world problems are rarely single objective but are multi-objective; therefore, multi-objective approaches should be given more attention and focus (Govindan et al., 2015 [4, 5]). Additionally, results are expected to be more informed, and better decisions are drawn when an appropriate structure of the problem and evaluation of the multi-criteria nature of the problem is explicitly established. Hence, multicriteria decision-making (MCDM) approaches are introduced in the current literature. In the field of remanufacturing, pertinent issues are successfully resolved using MCDM approaches such as: identifying a strategic model for distribution channel management using fuzzy analytical hierarchy process (FAHP) and hierarchical fuzzy technique for order of preference and similarity to ideal solutions (HFTOPSIS) (Paksoy et al., 2012 [20]), analyzing the interrelationships between risks faced by third-party logistics service providers (3PLs) using decision-making and trial evaluation laboratory (DEMATEL) (Govindan and Chaudhuri, 2016 [21]), and selecting important criteria in considering factors of reverse logistics implementation using FAHP (Chiou et al., 2012 [22]), to name a few. Given that the selection of a logistics center can be modeled as a decision problem that involves critical elements and that an integrated approach of simultaneously selecting distribution and collection centers lacks in the current literature, this paper aims to simultaneously identify a location for collection and distribution centers using MCDM approach. With an MCDM model, complexity and uncertainty of the selection process may mimic real-life decision-making with different and contradictory criteria and alternatives. Further, it is imperative to recognize that while the selection of collection and distribution centers are addressed in separate conditions,
doi:10.14743/apem2019.3.329 fatcat:3ah3jsdwa5be5pke7lau2pansu