B. Srirangacharyulu

Bio: B. Srirangacharyulu is an academic researcher from Indian Institute of Management Tiruchirappalli. The author has contributed to research in topics: Reverse logistics & Single-machine scheduling. The author has an hindex of 4, co-authored 5 publications receiving 194 citations. Previous affiliations of B. Srirangacharyulu include Indian Institute of Technology Madras.

A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics

Abstract: Due to green legislations, industries track the used products through reverse logistics contractors. A reverse logistics programme offers significant cost savings in procurement, transportation, disposal and inventory carrying. Since reverse logistics operations and the supply chains they support are considerably more complex than traditional manufacturing supply chains, it can be offered to third party contractors. But availability of more number of contractors make evaluating and selecting the most efficient Reverse Logistics Contractor (RLC) a challenging task and treated as a multi-criteria decision making problem. In this paper, a hybrid method using Analytical Hierarchy Process (AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is proposed. AHP is used to obtain the initial weights and Fuzzy TOPSIS is used to get the final ranking. A case study demonstrates the application of the proposed method. Finally sensitivity analysis is carried out to confirm the robustness.

A literature review and perspectives in reverse logistics

Abstract: In recent years, reverse logistics (RL) has become a field of importance for all organizations due to growing environmental concerns, legislation, corporate social responsibility and sustainable competitiveness. RL refers to the sequence of activities required to collect the used product from the customers for the purpose of either reuse or repair or re-manufacture or recycle or dispose of it. Perusal of the literature shows that research in the field of RL is in evolving phase and issues pertaining to adoption and implementation, forecasting product returns, outsourcing, RL networks from secondary market perspective, and disposition decisions have not been reviewed extensively. This study attempts to fill the existing gap through literature review on these issues, and outline the future directions for research based on research gap analysis. Total 242 published articles were selected, categorized, analyzed, and gaps in literature were identified to suggest for future research opportunities. The review may be useful for academicians, researchers and practitioners for better understanding of RL and guidance for future research.

Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria

Abstract: A third party reverse logistic provider (3PRLP) selection and evaluation process is developed.A multiple attribute decision making (MADM) model to evaluate and select 3PRLPs in the presence of risk factors is proposed.A fuzzy step-wise weight assessment ratio analysis (SWARA) approach to weight the evaluation criteria is applied.A fuzzy (COPRAS) is proposed to rank and select the sustainable third-party reverse logistics providers in the presence of risk factors.A real world case study is used from automotive industry to validate the quality of our model. Reverse logistics is the backward process of collecting and redistributing products at the end-of-life from customers to producers and manufacturers for reuse, remanufacturing and disposal purposes. While reverse logistics brings several economic benefits, it seems to become a necessity for businesses to remain competitive in a world that environmental and social aspects of business activities are key to sustainable development. The operations and management of reverse logistics systems is a complex task that requires substantial level of infrastructure, technology, expertise and experience. Therefore, increasingly many business organizations tend to outsource their reverse logistics activities to third-party reverse logistics providers (3PRLPs). In this paper, we propose a multiple attribute decision making (MADM) model to rank and select 3PRLPs, using fuzzy step-wise weight assessment ratio analysis (SWARA) to weight the evaluation criteria. Accordingly, a developed fuzzy complex proportional assessment of alternatives (COPRAS) was proposed to rank and select the sustainable 3PRLPs in the presence risk factors. The suggested model was applied to a case study from automotive industry. Eventually, COPRAS and COPRAS-G methods were considered for the purpose of comparison and validation. As a result, the most sustainable 3PRLP was selected. While incorporating risk factors into our analysis, our study shows that environmental and social drivers are increasingly becoming dominant when selecting 3PRLPs.