Using Differential Evolution to Develop a Carbon-Integrated Model for Performance Evaluation and Selection of Sustainabl
Automobile industries worldwide are unified in opinion, that successful management of sustainable supply chains is the most important driver to improve both their economic and ecological performances. The significance of sustainable supply chain managemen
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Abstract Automobile industries worldwide are unified in opinion, that successful management of sustainable supply chains is the most important driver to improve both their economic and ecological performances. The significance of sustainable supply chain management (SSCM) is a critical corporate matter in the automobile industries that offers incredible potential for achieving better environmental performance, consumer fulfillment, pull down operating expenditures, reducing inventory investments in addition to achieving better fixed asset usage. The environment concerns, climatic changes, and additional ecological concerns in automobile industries are not only articulated by campaigners or researchers, but also by the common man as well, which has motivated the industries to focus on sustainability. The present research focuses on a DEA-based mathematical model and employs differential evolution to select the competent suppliers providing the utmost fulfillment for the sustainable criteria determined. This study aims to examine the sustainable supplier evaluation and selection practices likely to be adopted by the Indian automobile industry for their products.
Keywords Sustainable supplier selection Differential evolution Data envelopment analysis Multi-criteria decision-making Sustainable supply chain management Automobile industry
S.K. Jauhar (&) M. Pant Indian Institute of Technology Roorkee, Roorkee, India e-mail: [email protected] M. Pant e-mail: [email protected] © Springer Science+Business Media Singapore 2016 M. Pant et al. (eds.), Proceedings of Fifth International Conference on Soft Computing for Problem Solving, Advances in Intelligent Systems and Computing 437, DOI 10.1007/978-981-10-0451-3_47
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1 Introduction Nowadays much focus is laid on environmental issues by government as well as by common man which has motivated the industries to think in the direction of sustainable supply chain paradigms. As a result, supplier selection problem which is an integral part of supply chain sustainability criterion has been considered [1–6]. Many researchers have discussed the importance of the nature of these decisions of sustainable supplier selection (SSS), which is usually difficult and unstructured [7]. Optimization practices might serve as useful tools for such decision-making problems. During last few years, differential evolution (DE) has risen as a dominant tool used for solving a variety of problems arising in various fields [8–13]. In this paper, we proposed a solution methodology for the SSS based on DE algorithm and data envelopment analysis (DEA), where DE is applied on SSS problem having DEA-based mathematical model. The approach is validated on a hypothetical case taken from Indian automobile industry while considering the environmental issues. The proposed approach is an extension of method introduced by the authors [14], which focuses on developing suitable supplier clusters. In [14] the authors have presented an approach for traditional supp
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