Application of Multi-Objective Optimization Based on Genetic Algorithm for Sustainable Strategic Supplier Selection under Fuzzy Environment

Purpose: The incorporation of environmental objective into the conventional supplier selection practices is crucial for corporations seeking to promote green supply chain management (GSCM). Challenges and risks associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. This paper aims to solve a Tetra “S” (SSSS) problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply chain environment. In this empirical study, a mathematical model with fuzzy coefficients is considered for sustainable strategic supplier selection (SSSS) problem and a corresponding model is developed to tackle this problem. Design/methodology/approach: Sustainable strategic supplier selection (SSSS) decisions are typically multi-objectives in nature and it is an important part of green production and supply chain management for many firms. The proposed uncertain model is transferred into deterministic model by applying the expected value measure (EVM) and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multiobjective optimization model for minimizing lean cost, maximizing sustainable service and greener product quality level. Finally, a mathematical case of textile sector is presented to exemplify the effectiveness of the proposed model with a sensitivity analysis. Findings: This study makes a certain contribution by introducing the Tetra ‘S’ concept in both the theoretical and practical research related to multi-objective optimization as well as in the study of sustainable strategic supplier selection (SSSS) under uncertain environment. Our results suggest that decision makers tend to select strategic supplier first then enhance the sustainability. Research limitations/implications: Although the fuzzy expected value model (EVM) with fuzzy coefficients constructed in present research should be helpful for solving real world problems. A detailed comparative analysis by using other algorithms is necessary for solving similar problems of agriculture, pharmaceutical, chemicals and services sectors in future. Practical implications: It can help the decision makers for ordering to different supplier for managing supply chain performance in efficient and effective manner. From the procurement and engineering perspectives, minimizing cost, sustaining the quality level and meeting production time line is the main consideration for selecting the supplier. Empirically, this can facilitate engineers to reduce production costs and at the same time improve the product quality. Originality/value: In this paper, we developed a novel multi-objective programming model based on genetic algorithm to select sustainable strategic supplier (SSSS) under fuzzy environment. The algorithm was tested and applied to solve a real case of textile sector in Pakistan. The experimental results and comparative sensitivity analysis illustrate the effectiveness of our proposed model.Peer Reviewe

How supplier selection criteria affects business performance? A study of UK automotive sector

According to KPMG international (2015), global sales of automobiles are forecasted to reach 73.9 million vehicles and expected to hit 100 million units in the next two years. This shows that automotive sector has a tremendous growth potential and UK automotive sector is no different. However, in recent years the growing environmental awareness has become a major concern for automotive sector as they are faced with pressure of reducing carbon emissions as well as the costs. Suppliers play a significant role in achieving environmental goals set by organisations. Under these circumstances it is worth exploring the criteria that are used in assessing suppliers including the green aspects and how that affects the business performance. Design/methodology/approach: This research adopts a mixed method research approach. In order to collect the quantitative data a survey questionnaire was constructed and sent to automotive businesses listed in the FAME database. In order to triangulate the findings of this study, survey was complemented with in-depth interviews. Around 100 automotive manufacturers were invited for the survey however only 38 usable responses were received. In total seven semi-structured interviews were also conducted with people from different backgrounds and work experiences in the automotive sector. Findings: Literature identified delivery, cost, quality and technology as the supplier assessment criteria commonly used in assessing suppliers in automotive industries. Yet the issue of culture and green supply chain practices (GSP) were also widely concerned in several studies. The data analysis showed that delivery, quality, cost, technology, culture are correlated with exception of green supply chain practices. GSP was only found to be correlated with technology and cultural criteria. Semi-structured interviews suggest delivery and quality as the most important criteria when assessing supplier because of their greater impact toward business performance and reputation. Findings from all respondents also showed that most automotive manufacturers have already adopted environmental competency in their criteria. However, interviewees mentioned that this criterion does not take a major role in assessment compared with other criteria. The results also indicate that all factors studied do affect the business performance of automotive organisations. Value: This study contributes to the limited literature focused on assessing supplier selection criteria and business performance linkage in the UK automotive organisations. In addition, most studies on supplier selection and business performance ignore the green practices as important criteria which this study aims to address. Research limitations/implications: The study is based on the findings from a limited survey responses and semi-structured interviews. Having larger sample population would certainly improve the validity of the findings. The perspective of SMEs and large businesses with regard to each supplier selection criterion may be different hence the future research in this domain would also provide some valuable contributions. Practical implications: The survey responses indicate green supply practices as one of the important criteria in supplier selection. This suggests that automotive manufacturers should realize the importance of green practices while selecting their suppliers. This will help them to meet their own green goals while simultaneously meeting the government environmental.Ministry of Science and Technology, Taiwan ▪ Economic Development Bureau, Kaohsiung, Taiwan ▪ National Kaohsiung First University of Science & Tech, Taiwan ▪ National Taiwan Ocean University, Taiwan ▪ Taiwan International Ports Corp. Ltd. ▪ Jade Yachts Shipbuilding Co., Ltd. ▪ International Academy for Marine Economy and Technology, The University of Nottingham Ningbo Campus, China ▪ The Institute for Advanced Manufacturing, The University of Nottingham, U

Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies

[EN] Supplier evaluation is a relevant task of supply chain management where multicriteria methods make great contributions to manufacturing industries. This is not the case in food distribution companies, which have a key role in providing safe and affordable food to society. The purpose of this research is to measure the sustainability of products and suppliers in food distribution companies through a multiple criteria approach. Firstly, the system proposed provides indicators to qualify products and assess the food quality, using the compensatory Multi-Attribute Utility Theory (MAUT) model. Secondly, these indicators are included in supplier evaluation, which takes economic, environmental, and social criteria into account. MAUT and Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE), a non-compensatory method, are used for supplier evaluation. This approach has been validated for fresh food in a supermarket chain, mainly using historical data. Partial indicators, such as food safety scores, together with global indicators of suppliers, inform the most appropriate decisions and the most appropriate relations between companies and providers. Poor performance in food safety can lead to the disqualification of some suppliers. MAUT is good for qualifying products and is easy to apply at the operational level in logistic platforms, while PROMETHEE is more suitable for supplier segmentation, as it helps to identify supplier strengths and weaknesses.This research was funded by the Regional Ministry of Education, Research, Culture and Sport of the Autonomous Government of the Valencian Region, Spain, grant number AICO/2017/066.Segura Maroto, M.; Maroto Álvarez, MC.; Segura García Del Río, B. (2019). Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies. Sustainability. 11(21):1-18. https://doi.org/10.3390/su11215875S1181121Thies, C., Kieckhäfer, K., Spengler, T. S., & Sodhi, M. S. (2019). Operations research for sustainability assessment of products: A review. European Journal of Operational Research, 274(1), 1-21. doi:10.1016/j.ejor.2018.04.039Diaz-Balteiro, L., González-Pachón, J., & Romero, C. (2017). Measuring systems sustainability with multi-criteria methods: A critical review. European Journal of Operational Research, 258(2), 607-616. doi:10.1016/j.ejor.2016.08.075Zimmer, K., Fröhling, M., & Schultmann, F. (2015). Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. International Journal of Production Research, 54(5), 1412-1442. doi:10.1080/00207543.2015.1079340Chai, J., & Ngai, E. W. T. (2020). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, 140, 112903. doi:10.1016/j.eswa.2019.112903Chai, J., Liu, J. N. K., & Ngai, E. W. T. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872-3885. doi:10.1016/j.eswa.2012.12.040Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98, 66-83. doi:10.1016/j.jclepro.2013.06.046Ansari, Z. N., & Kant, R. (2017). A state-of-art literature review reflecting 15 years of focus on sustainable supply chain management. Journal of Cleaner Production, 142, 2524-2543. doi:10.1016/j.jclepro.2016.11.023Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16-24. doi:10.1016/j.ejor.2009.05.009Rajeev, A., Pati, R. K., Padhi, S. S., & Govindan, K. (2017). Evolution of sustainability in supply chain management: A literature review. Journal of Cleaner Production, 162, 299-314. doi:10.1016/j.jclepro.2017.05.026Demir, L., Akpınar, M. E., Araz, C., & Ilgın, M. A. (2018). A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT. Expert Systems with Applications, 114, 479-487. doi:10.1016/j.eswa.2018.07.071Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 62, 273-283. doi:10.1016/j.eswa.2016.06.030Chang, L., Ouzrout, Y., Nongaillard, A., Bouras, A., & Jiliu, Z. (2014). Multi-criteria decision making based on trust and reputation in supply chain. International Journal of Production Economics, 147, 362-372. doi:10.1016/j.ijpe.2013.04.014Ekici, A. (2013). An improved model for supplier selection under capacity constraint and multiple criteria. International Journal of Production Economics, 141(2), 574-581. doi:10.1016/j.ijpe.2012.09.013Lin, R.-H. (2012). An integrated model for supplier selection under a fuzzy situation. International Journal of Production Economics, 138(1), 55-61. doi:10.1016/j.ijpe.2012.02.024Amid, A., Ghodsypour, S. H., & O’Brien, C. (2011). A weighted max–min model for fuzzy multi-objective supplier selection in a supply chain. International Journal of Production Economics, 131(1), 139-145. doi:10.1016/j.ijpe.2010.04.044Chen, Y.-J. (2011). Structured methodology for supplier selection and evaluation in a supply chain. Information Sciences, 181(9), 1651-1670. doi:10.1016/j.ins.2010.07.026Zeydan, M., Çolpan, C., & Çobanoğlu, C. (2011). A combined methodology for supplier selection and performance evaluation. Expert Systems with Applications, 38(3), 2741-2751. doi:10.1016/j.eswa.2010.08.064Şen, C. G., Baraçlı, H., Şen, S., & Başlıgil, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Applications, 36(3), 5272-5283. doi:10.1016/j.eswa.2008.06.070Bottani, E., & Rizzi, A. (2008). An adapted multi-criteria approach to suppliers and products selection—An application oriented to lead-time reduction. International Journal of Production Economics, 111(2), 763-781. doi:10.1016/j.ijpe.2007.03.012Govindan, K., Kadziński, M., & Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, 71, 129-145. doi:10.1016/j.omega.2016.10.004Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. doi:10.1016/j.omega.2014.11.009Rezaei, J., & Ortt, R. (2013). Multi-criteria supplier segmentation using a fuzzy preference relations based AHP. European Journal of Operational Research, 225(1), 75-84. doi:10.1016/j.ejor.2012.09.037Segura, M., & Maroto, C. (2017). A multiple criteria supplier segmentation using outranking and value function methods. Expert Systems with Applications, 69, 87-100. doi:10.1016/j.eswa.2016.10.031Bloemhof, J. M., & Soysal, M. (2016). Sustainable Food Supply Chain Design. Springer Series in Supply Chain Management, 395-412. doi:10.1007/978-3-319-29791-0_18Grimm, J. H., Hofstetter, J. S., & Sarkis, J. (2014). Critical factors for sub-supplier management: A sustainable food supply chains perspective. International Journal of Production Economics, 152, 159-173. doi:10.1016/j.ijpe.2013.12.011Lau, H., Nakandala, D., & Shum, P. K. (2018). A business process decision model for fresh-food supplier evaluation. Business Process Management Journal, 24(3), 716-744. doi:10.1108/bpmj-01-2016-0015Beske, P., Land, A., & Seuring, S. (2014). Sustainable supply chain management practices and dynamic capabilities in the food industry: A critical analysis of the literature. International Journal of Production Economics, 152, 131-143. doi:10.1016/j.ijpe.2013.12.026Schmitt, E., Galli, F., Menozzi, D., Maye, D., Touzard, J.-M., Marescotti, A., … Brunori, G. (2017). Comparing the sustainability of local and global food products in Europe. Journal of Cleaner Production, 165, 346-359. doi:10.1016/j.jclepro.2017.07.039Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200(1), 198-215. doi:10.1016/j.ejor.2009.01.021The PROMETHEE Bibliographical Databasehttp://www.promethee-gaia.net/bibliographical-database.htmlChen, Y.-H., Wang, T.-C., & Wu, C.-Y. (2011). Strategic decisions using the fuzzy PROMETHEE for IS outsourcing. Expert Systems with Applications, 38(10), 13216-13222. doi:10.1016/j.eswa.2011.04.137Araz, C., & Ozkarahan, I. (2007). Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. International Journal of Production Economics, 106(2), 585-606. doi:10.1016/j.ijpe.2006.08.008Dulmin, R., & Mininno, V. (2003). Supplier selection using a multi-criteria decision aid method. Journal of Purchasing and Supply Management, 9(4), 177-187. doi:10.1016/s1478-4092(03)00032-3Seuring, S. (2013). A review of modeling approaches for sustainable supply chain management. Decision Support Systems, 54(4), 1513-1520. doi:10.1016/j.dss.2012.05.053Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2014). Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 233(2), 299-312. doi:10.1016/j.ejor.2013.09.032Xu, Z. (2000). On consistency of the weighted geometric mean complex judgement matrix in AHP. European Journal of Operational Research, 126(3), 683-687. doi:10.1016/s0377-2217(99)00082-xKonys. (2019). Green Supplier Selection Criteria: From a Literature Review to a Comprehensive Knowledge Base. Sustainability, 11(15), 4208. doi:10.3390/su11154208D-Sight CDMhttp://www.d-sight.com/solutions/d-sight-cd

Improving Food Supply Chain Management by a Sustainable Approach to Supplier Evaluation

[EN] Increasing food supply chain sustainability means having to deal with many conflicting aspects and involves producers, several departments in distribution companies, and consumers. The objectives of this research are to develop models to solve real-world supplier evaluation problems and validate them with real data on fresh fruits in a supermarket chain. Literature review and results from a survey with managers from purchasing, logistics, and quality departments of a food distribution company are used to establish criteria, to first model the assessment of products and, second, to model supplier evaluation. A multicriteria hybrid approach is proposed, using multi-attribute utility theory (MAUT) to assess the quality of products and Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) to complete their evaluation with strategic criteria to be included in the second phase. The results allow companies to rank suppliers by product and classify them according to the main criteria categories, such as product strategy, food safety, economic, logistic, commercial, green image and corporate social responsibility. A sorting approach is also applied to obtain ordered groups of suppliers. Finally, the models proposed can form the core of a decision support system in order to create and monitor the supplier base in food distribution companies, as well as to inform sustainable decision making.This research was funded by the Regional Ministry of Education, Research, Culture and Sport of the Autonomous Government of the Valencian Region, Spain, grant number AICO/2017/066.Segura Maroto, M.; Maroto Álvarez, MC.; Segura García Del Río, B.; Casas-Rosal, JC. (2020). Improving Food Supply Chain Management by a Sustainable Approach to Supplier Evaluation. Mathematics. 8(11):1-23. https://doi.org/10.3390/math8111952S123811Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16-24. doi:10.1016/j.ejor.2009.05.009Zimmer, K., Fröhling, M., & Schultmann, F. (2015). Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. International Journal of Production Research, 54(5), 1412-1442. doi:10.1080/00207543.2015.1079340Aouadni, S., Aouadni, I., & Rebaï, A. (2019). A systematic review on supplier selection and order allocation problems. Journal of Industrial Engineering International, 15(S1), 267-289. doi:10.1007/s40092-019-00334-yChai, J., Liu, J. N. K., & Ngai, E. W. T. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872-3885. doi:10.1016/j.eswa.2012.12.040Chai, J., & Ngai, E. W. T. (2020). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, 140, 112903. doi:10.1016/j.eswa.2019.112903Wetzstein, A., Hartmann, E., Benton jr., W. C., & Hohenstein, N.-O. (2016). A systematic assessment of supplier selection literature – State-of-the-art and future scope. International Journal of Production Economics, 182, 304-323. doi:10.1016/j.ijpe.2016.06.022Ansari, Z. N., & Kant, R. (2017). A state-of-art literature review reflecting 15 years of focus on sustainable supply chain management. Journal of Cleaner Production, 142, 2524-2543. doi:10.1016/j.jclepro.2016.11.023Schramm, V. B., Cabral, L. P. B., & Schramm, F. (2020). Approaches for supporting sustainable supplier selection - A literature review. Journal of Cleaner Production, 273, 123089. doi:10.1016/j.jclepro.2020.123089Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98, 66-83. doi:10.1016/j.jclepro.2013.06.046Rajeev, A., Pati, R. K., Padhi, S. S., & Govindan, K. (2017). Evolution of sustainability in supply chain management: A literature review. Journal of Cleaner Production, 162, 299-314. doi:10.1016/j.jclepro.2017.05.026Demir, L., Akpınar, M. E., Araz, C., & Ilgın, M. A. (2018). A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT. Expert Systems with Applications, 114, 479-487. doi:10.1016/j.eswa.2018.07.071Diaz-Balteiro, L., González-Pachón, J., & Romero, C. (2017). Measuring systems sustainability with multi-criteria methods: A critical review. European Journal of Operational Research, 258(2), 607-616. doi:10.1016/j.ejor.2016.08.075Thies, C., Kieckhäfer, K., Spengler, T. S., & Sodhi, M. S. (2019). Operations research for sustainability assessment of products: A review. European Journal of Operational Research, 274(1), 1-21. doi:10.1016/j.ejor.2018.04.039Konys. (2019). Green Supplier Selection Criteria: From a Literature Review to a Comprehensive Knowledge Base. Sustainability, 11(15), 4208. doi:10.3390/su11154208Segura, M., Maroto, C., & Segura, B. (2019). Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies. Sustainability, 11(21), 5875. doi:10.3390/su11215875Memari, A., Dargi, A., Akbari Jokar, M. R., Ahmad, R., & Abdul Rahim, A. R. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of Manufacturing Systems, 50, 9-24. doi:10.1016/j.jmsy.2018.11.002Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 62, 273-283. doi:10.1016/j.eswa.2016.06.030Chang, L., Ouzrout, Y., Nongaillard, A., Bouras, A., & Jiliu, Z. (2014). Multi-criteria decision making based on trust and reputation in supply chain. International Journal of Production Economics, 147, 362-372. doi:10.1016/j.ijpe.2013.04.014Ekici, A. (2013). An improved model for supplier selection under capacity constraint and multiple criteria. International Journal of Production Economics, 141(2), 574-581. doi:10.1016/j.ijpe.2012.09.013Lin, R.-H. (2012). An integrated model for supplier selection under a fuzzy situation. International Journal of Production Economics, 138(1), 55-61. doi:10.1016/j.ijpe.2012.02.024Amid, A., Ghodsypour, S. H., & O’Brien, C. (2011). A weighted max–min model for fuzzy multi-objective supplier selection in a supply chain. International Journal of Production Economics, 131(1), 139-145. doi:10.1016/j.ijpe.2010.04.044Chen, Y.-J. (2011). Structured methodology for supplier selection and evaluation in a supply chain. Information Sciences, 181(9), 1651-1670. doi:10.1016/j.ins.2010.07.026Zeydan, M., Çolpan, C., & Çobanoğlu, C. (2011). A combined methodology for supplier selection and performance evaluation. Expert Systems with Applications, 38(3), 2741-2751. doi:10.1016/j.eswa.2010.08.064Şen, C. G., Baraçlı, H., Şen, S., & Başlıgil, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Applications, 36(3), 5272-5283. doi:10.1016/j.eswa.2008.06.070Bottani, E., & Rizzi, A. (2008). An adapted multi-criteria approach to suppliers and products selection—An application oriented to lead-time reduction. International Journal of Production Economics, 111(2), 763-781. doi:10.1016/j.ijpe.2007.03.012Segura, M., & Maroto, C. (2017). A multiple criteria supplier segmentation using outranking and value function methods. Expert Systems with Applications, 69, 87-100. doi:10.1016/j.eswa.2016.10.031Trapp, A. C., & Sarkis, J. (2016). Identifying Robust portfolios of suppliers: a sustainability selection and development perspective. Journal of Cleaner Production, 112, 2088-2100. doi:10.1016/j.jclepro.2014.09.062Araz, C., & Ozkarahan, I. (2007). Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. International Journal of Production Economics, 106(2), 585-606. doi:10.1016/j.ijpe.2006.08.008Boran, F. E., Genç, S., Kurt, M., & Akay, D. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363-11368. doi:10.1016/j.eswa.2009.03.039Zopounidis, C., & Doumpos, M. (2002). Multicriteria classification and sorting methods: A literature review. European Journal of Operational Research, 138(2), 229-246. doi:10.1016/s0377-2217(01)00243-0Brans, J. P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The Promethee method. European Journal of Operational Research, 24(2), 228-238. doi:10.1016/0377-2217(86)90044-5Nemery, P., & Lamboray, C. (2007). ℱlow $\mathcal{S}$ ort: a flow-based sorting method with limiting or central profiles. TOP, 16(1), 90-113. doi:10.1007/s11750-007-0036-xLau, H., Nakandala, D., & Shum, P. K. (2018). A business process decision model for fresh-food supplier evaluation. Business Process Management Journal, 24(3), 716-744. doi:10.1108/bpmj-01-2016-0015D-Sight CDM http://www.d-sight.com/solutions/d-sight-cdmNemery, P., Lidouh, K., & Mareschal, B. (2011). On the usefulness of taking the weights into account in the GAIA visualisations. International Journal of Information and Decision Sciences, 3(3), 228. doi:10.1504/ijids.2011.041585Nemery, P., Ishizaka, A., Camargo, M., & Morel, L. (2012). Enriching descriptive information in ranking and sorting problems with visualizations techniques. Journal of Modelling in Management, 7(2), 130-147. doi:10.1108/17465661211242778Xu, Z. (2000). On consistency of the weighted geometric mean complex judgement matrix in AHP. European Journal of Operational Research, 126(3), 683-687. doi:10.1016/s0377-2217(99)00082-xOrtiz‐Barrios, M., Miranda‐De la Hoz, C., López‐Meza, P., Petrillo, A., & De Felice, F. (2019). A case of food supply chain management with AHP, DEMATEL, and TOPSIS. Journal of Multi-Criteria Decision Analysis, 27(1-2), 104-128. doi:10.1002/mcda.169

Multi-objective optimization for Green Supply Chain Management and Design : Application to the orange juice agrofood cluster

Supply chain and operations management has matured from a field that addressed only operational and economic concerns to one that comprehensively considers the broader environmental and social issues that face industrial organizations of today. Adding the term “green” to supply chain activities seeks to incorporate environmentally conscious thinking in all processes in the supply chain. The aim of this work is to develop a Green Supply Chain (GrSC) framework based on a multi-objective optimization approach, with specific emphasis on agrofood supply chain design, planning and operations through the implementation of appropriate green supply chain management and logistics principles. The case study is the orange juice cluster. The research objective is the minimization of the environmental burden and the maximization of economic profitability of the selected product categories. This work focuses on the application of GrSCM to two fundamental strategic issues targeting agro food supply chains. The former is related to the Green Supplier Selection (GSS) problem devoted to the farming production systems and the way they are integrated into the global supply chain network. The latter focuses on the global Green Supply Chain Network Design (GSCND) as a whole. These two complementary and ultimately integrated strategic topics are framed in order to evaluate and exploit the unique characteristics of agro food supply chains in relation to eco-labeling. The methodology is based on the use of Life Cycle Assessment, Multi-objective Optimization via Genetic Algorithms and Multiple-criteria Decision Making tools (TOPSIS type). The approach is illustrated and validated through the development and analysis of an Orange Juice Supply Chain case study modelled as a three echelon GrSC composed of the supplier, manufacturing and market levels that in turn are decomposed into more detailed subcomponents. Methodologically, the work has shown the development of the modelling and optimization GrSCM framework is useful in the context of eco-labeled agro food supply chain and feasible in particular for the orange juice cluster. The proposed framework can help decision makers handle the complexity that characterizes agro food supply chain design decision and that is brought on by the multi-objective and multi-period nature of the problem as well as by the multiple stakeholders, thus preventing to make the decision in a segmented empirical manner. Experimentally, under the assumptions used in the case study, the work highlights that by focusing only on the “organic” eco-label to improve the agricultural aspect, low to no improvement on overall supply chain environmental performance is reached in relative terms. In contrast, the environmental criteria resulting from a full lifecycle approach is a better option for future public and private policies to reach more sustainable agro food supply chains

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Improving sustainability performance through supplier relationship management in the tobacco industry

Purpose: The purpose of this study is to explore how tobacco manufacturing companies can improve their sustainability performance via effective supplier relationship management (SRM). Design/methodology/approach: This study has adopted a single case study of an international tobacco company. The primary data involved semi-structured interviews with participants from the case company who are familiar with sustainable SRM in the tobacco industry and are engaging in various techniques to improve sustainability performance. Findings: The drivers for sustainable SRM commonly identified in literature are observable within the case company. There is also clear evidence of integrating sustainability in its SRM processes. However, the perception of sustainability as a requirement to meet stringent regulations limits its scope and drive in pursuing sustainable SRM. It has also limited supplier sustainability evaluation and performance metrics. Furthermore, the findings of this paper reinforce the importance of a procurement team’s ability to work with other functional teams in implementing sustainable SRM. The findings also contribute to the emerging literature on the impact of sustainability on supplier segmentation and multi-tier supplier management. Research limitations/implications: This study provides insight into the varying SRM methods used in the tobacco industry to ensure compliance and improve sustainability performance. However, further research is required to explore the generalisability of the findings of this study derived from a single case study. Originality/value: The tobacco industry is an under-researched industry, particularly in terms of sustainable operations and supply chain management practices. The findings of this study seem to be relevant to those comparable industries with stringent regulations as well

Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process

The proposed system illustrates that logic fuzzy can be used to aid management in assessing a supplier's environmental performance in the supplier selection process. A user-centred hierarchical system employing scalable fuzzy membership functions implement human priorities in the supplier selection process, with particular focus on a supplier's environmental performance. Traditionally, when evaluating supplier performance, companies have considered criteria such as price, quality, flexibility, etc. These criteria are of varying importance to individual companies pertaining to their own specific objectives. However, with environmental pressures increasing, many companies have begun to give more attention to environmental issues and, in particular, to their suppliers’ environmental performance. The framework presented here was developed to introduce efficiently environmental criteria into the existing supplier selection process and to reflect on its relevant importance to individual companies. The system presented attempts to simulate the human preference given to particular supplier selection criteria with particular focus on environmental issues when considering supplier selection. The system considers environmental data from multiple aspects of a suppliers business, and based on the relevant impact this will have on a Buying Organization, a decision is reached on the suitability of the supplier. This enables a particular supplier's strengths and weaknesses to be considered as well as considering their significance and relevance to the Buying OrganizationPeer reviewe

To Greener Pastures: An Action Research Study on the Environmental Sustainability of Humanitarian Supply Chains

Purpose: While humanitarian supply chains (HSCs) inherently contribute to social sustainability by alleviating the suffering of afflicted communities, their unintended adverse environmental impact has been overlooked hitherto. This paper draws upon contingency theory to synthesize green practices for HSCs, identify the contingency factors that impact on greening HSCs and explore how focal humanitarian organizations (HOs) can cope with such contingency factors. Design/methodology/approach: Deploying an action research methodology, two-and-a-half cycles of collaboration between researchers and a United Nations agency were completed. The first half-cycle developed a deductive greening framework, synthesizing extant green practices from the literature. In the second and third cycles, green practices were adopted/customized/developed reflecting organizational and contextual contingency factors. Action steps were implemented in the HSC for prophylactics, involving an operational mix of disaster relief and development programs. Findings: First, the study presents a greening framework that synthesizes extant green practices in a suitable form for HOs. Second, it identifies the contingency factors associated with greening HSCs regarding funding environment, stakeholders, field of activity and organizational management. Third, it outlines the mechanisms for coping with the contingency factors identified, inter alia, improving the visibility of headquarters over field operations, promoting collaboration and resource sharing with other HOs as well as among different implementing partners in each country, and working with suppliers for greener packaging. The study advances a set of actionable propositions for greening HSCs. Practical implications: Using an action research methodology, the study makes strong practical contributions. Humanitarian practitioners can adopt the greening framework and the lessons learnt from the implementation cycles presented in this study. Originality/value: This is one of the first empirical studies to integrate environmental sustainability and HSCs using an action research methodology

Sustainable supply chain management needs sustainable logistics services. The strategic role played by logistics service providers

Purpose – The purpose of this research is to examine the concept of sustainable service co-creation in triadic business relationships in logistics and supply chain management. More companies seek to develop sustainable solutions that would not be sustainable exclusively for themselves but for the supply chain they belong to. In doing that – especially when dealing with services – they may need the external support from logistics service providers (LSPs). This paper aims to explore the innovative initiatives undertaken by LSPs in triadic relationship management with their customers and suppliers while co-creating sustainable services along the supply chain. Design/methodology/approach – To investigate the research question, a systematic literature review and empirical exploratory investigation through case study will be conducted adopting the qualitative methodology, to explore trends and evolving paradigms. Findings – A literature review conducted in this paper enriches existing literature through an integration of sustainability in a viable system approach and logistics service provision, in particular, it investigates the ways in which sustainability is achieved. It is assumed that the triadic relationship among an LSP and its customers and suppliers requires significant modifications in collaboration and an innovative approach in operating procedures. Research limitations/implications – This paper is an exploratory study and limited in its scope to an example of a relationship that focuses mainly on three actors: the supplier, the LSP and the customer. However, it could be extended in terms of numbers of case studies investigated. Practical implications – The implications arising from the literature and the empirical research offer a range of current sustainable practices in the services sector. This could be a starting point for other research and company activities. Originality/value – There is little research that addresses the issue of sustainability and logistics service providers simultaneously, hence the present paper is meant to fill the gap by providing a foundation which actors of different supply chains could use as a benchmark. This study gives evidence of how logistics services may contribute to sustainable development. Key words – sustainable supply chain management, logistics service providers, viable system approach, co-creation, business relationship managemen