Amir Hossein Azadnia

Sustainable supplier selection and order lot-sizing: An integrated multi-objective decision-making process

Within supply chains activities, selecting appropriate suppliers based on the sustainability criteria (economic, environmental and social) can help companies move toward sustainable development. Although several studies have recently been accomplished to incorporate sustainability criteria into supplier selection problem, much less attention has been devoted to developing a comprehensive mathematical model that allocates the optimal quantities of orders to suppliers considering lot-sizing problems. In this research, we propose an integrated approach of rule-based weighted fuzzy method, fuzzy analytical hierarchy process and multi-objective mathematical programming for sustainable supplier selection and order allocation combined with multi-period multi-product lot-sizing problem. The mathematical programming model consists of four objective functions which are minimising total cost, maximising total social score, maximising total environmental score and maximising total economic qualitative score. The proposed model is developed based on the parameters achieved through the preprocessing of suppliers’ social, environmental and economic data by a rule-based weighted fuzzy approach and fuzzy analytical hierarchy process. The proficiency and applicability of the proposed approach is illustrated by a case study of packaging films in food industry. Considering sustainability criteria in the proposed model reveals that a higher value of sustainable purchasing is achievable in comparison with a single-objective cost-based model.

Order batching in warehouses by minimizing total tardiness: a hybrid approach of weighted association rule mining and genetic algorithms.

One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.

An integrated approach for sustainable supplier selection using fuzzy logic and fuzzy AHP

Supplier selection is one of the important processes in supply chain management. Regarding the emergence of sustainability issues in recent decades, companies have incorporated these issues in conventional supplier selection in order to meet governmental legislations and market demands. These issues have been noticed by various researchers. However, there are limited research activities which considered all aspects of sustainability for supplier selection problem as an integrated assessment. In this paper, an integrated approach of Fuzzy Analytical Hierarchy Process and fuzzy logic has been proposed in order to solve sustainable supplier selection problem. Fuzzy analytical hierarchy process has been used to calculate the weight of sustainable criteria and sub criteria. Then, fuzzy logic was utilized in order to assess the suppliers based on the weights acquired by Fuzzy analytical hierarchy process. Finally, a case study of petroleum industry has been carried out in order to show the validity of proposed approach.

A review on the buyer–supplier dyad relationships in sustainable procurement context: past, present and future

Sustainable development is currently being applied in most fields of research. Procurement, focused on the buyer–supplier dyad, is one such discipline where sustainability is being widely applied. This paper provides a review of these research studies, conducting a systematic content analysis in order to present the state of the art in this domain. The paper carries out a detailed review of articles in international scientific journals and well-known international conferences related to green and sustainable supplier selection published between 2008 and 2014 inclusive. Seven designed research questions are proposed and answered based on this bibliography. Interesting results are reported in each section and gaps in the current body of literature are identified. The purpose of this review is to provide important future directions and limitations in this research topic.

Supplier Selection: A Hybrid Approach Using ELECTRE and Fuzzy Clustering

Vendor selection is a strategic issue in supply-chain management for any organization to identify the right supplier. Such selection in most cases is based on the analysis of some specific criteria. Most of the researches so far concentrate on multi-criteria decision making (MCDM) analysis. However, it incurs a huge computational complexity when a large number of suppliers are considered. So, data mining approaches would be required to convert raw data into useful information and knowledge. Hence, a new hybrid model of MCDM and data mining approaches was proposed in this research to address the supplier selection problem. In this paper, Fuzzy C-Means (FCM) clustering as a data mining model has been used to cluster suppliers into groups. Then, Elimination and Choice Expressing Reality (ELECTRE) method has been employed to rank the suppliers. The efficiency of this method was revealed by conducting a case study in an automotive industry.

A Hybrid Fuzzy MCDM Approach for Sustainable Third-Party Reverse Logistics Provider Selection

Third-party reverse logistics providers (3PRLPs) selection has become an important logistics function which can help companies to maintain their competitive edge. Traditionally, companies solely considered economic aspects for selecting their 3PRLPs. However, due to increased pressure from different types of stakeholders regarding environmental and social issues in recent years, companies have been obliged to incorporate these issues in their logistics and supply chains functions. Although many studies have been conducted in the field of 3PRLPs selection, much less attention has been devoted to incorporating all three aspects of sustainability (social, environmental, and economic) in this field. In this research, a hybrid fuzzy multi-criteria decision-making (FMCDM) approach is proposed for selecting 3PRLPs while all three dimensions of sustainability were taken into account. Fuzzy analytic hierarchy process (FAHP) was used in order to weight the selected sustainability criteria and subcriteria. Then, fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) was applied for determining the ranking of suppliers. The applicability of the proposed approach was tested in an electronic manufacturing company.

Order Processing in Supply Chain Management with Developing an Information System Model: An Automotive Manufacturing Case Study

Nowadays, high competitive market needs fast, effective, high responsiveness, online interactive, 24 hours 7 days availability and easy to follow up order processing. Consequently, there is a need for a model in which interdisciplinary approaches for understanding the range of Supply Chain Management (SCM) Information System (IS) capabilities are provided. In this study, an integrated model of SCM IS was developed that is supported by empirical evidence specific to SCM IS implementations. The developed model integrates and enriches theories of competitive strategy, supply chain management and inter-organizational information systems. Then, a case study of an automotive manufacturing industry was conducted to demonstrate the proficiency of the proposed model. As a result, better understanding of capabilities of implemented supply chain management information systems and expected future capabilities could be identified by practitioners and decision makers. Finally, findings of this study are listed together with some future works.

Sustainability assessment methodology for concrete manufacturing process: A fuzzy inference system approach

Sustainability assessment of concrete manufacturing processes has recently received great attention among scholars and practitioners. While most of the studies on sustainability assessment of concrete manufacturing processes focus on economic and environmental issues, those which consider all three dimensions of sustainability (social, economic, and environmental) simultaneously are rather limited. In this study, a hybrid approach of fuzzy inference system and analytical hierarchy process (AHP) is proposed in order to evaluate the sustainability level of concrete manufacturing processes based on Life Cycle Assessment (LCA) principals. AHP is applied to weight the selected sustainability elements and sub elements. Afterward, fuzzy inference system is used to evaluate the sustainability level of concrete manufacturing processes. The practicality and applicability of the proposed approach are examined by conducting sustainability assessments of four different concrete manufacturing processes: (1) 100% of Portland cement (2) 35 % slag cement and 65% Portland cement (3) 50% slag cement and 50% Portland cement (4) 20% fly ash and 80% Portland cement. The results disclose the more sustainable concrete manufacturing process which is 50 % of Slag cement and 50% Portland cement.

A Simulation Study on Bullwhip Effect in Supply Chain Based on Theory of Constraint

TOC offers a proposal that is complementary in many aspects and very distinguishable in others about the way some key processes and elements of supply chain management (SCM) are managed, especially outbound logistics. This chapter deals with the paradigm that “TOC diminishes the forecasts in supply chain management by its buffer management strategy to handle difficulties”. Developing a model and examining it with simulation is helpful to investigate and evaluate the contribution of TOC to supply chain management. To our knowledge, the proposed basic model is the first model to consider such viewpoints by TOC and opens new doors to more research on this area.