A hybrid algorithm for managing green performance in supply chain using SWOT approach, by combining MCDM techniques in grey conditions

2022 ◽  
Vol 15 (1) ◽  
pp. 62
Author(s):  
Ali Nazeri ◽  
Samin Ghanavatinejad ◽  
Seyed Mohamad Mahdi Kazemi ◽  
Zahra Tabatabaei
Keyword(s):  
Supply Chain ◽  
Hybrid Algorithm ◽  
Green Performance

A hybrid algorithm for managing green performance in supply chain using SWOT approach, by combining MCDM techniques in gray conditions

2020 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Zahra Tabatabaei ◽  
Ali Nazeri ◽  
Seyed Mohammad Mehdi Kazemi ◽  
Samin Ghanavati
Keyword(s):  
Supply Chain ◽  
Hybrid Algorithm ◽  
Green Performance

A quantitative framework for lean and green assessment of supply chain performance

2018 ◽  
Vol 67 (2) ◽  
pp. 366-400 ◽  
Author(s):  
Shashank Thanki ◽  
Jitesh Thakkar
Keyword(s):  
Supply Chain ◽  
Performance Measures ◽  
Value Chain ◽  
Evaluation Framework ◽  
Fuzzy Decision Making ◽  
Causal Relationships ◽  
Assessment Framework ◽  
Content Type ◽  
Green Performance ◽  
Lean And Green

Purpose The purpose of this paper is to propose a balanced scorecard (BSC)- and strategy map-based quantitative framework for assessing the lean and green performance of the supply chain (SC). As the SC competitiveness demands efficient and effective utilization of resources throughout the value chain, not only adoption of lean and green SC paradigms but simultaneously its performance evaluation is also vital. Design/methodology/approach The lean and green SC performance measures are classified into four categories of BSC. A fuzzy decision-making trial and evaluation laboratory (DEMATEL) methodology combined with analytical network process is proposed for examining the causal relationships between BSC perspectives and respective assessment criteria. The application of the proposed assessment framework is demonstrated for the case of Indian textile SC. Findings The research delivers a quantitative assessment framework for evaluating lean and green performance of the SC. The results obtained for a typical case of Indian textile SC revealed that “delivery performance,” “profitability” and “operational cost” are the most crucial performance measures. The perspective of “internal processes” is the most significant of all BSC perspectives while “learning and growth” perspective acts as the driving force to improve lean and green SC performance. Originality/value The paper makes two contributions in the domain of lean and green assessment of SC performance. First, it proposes an evaluation framework to investigate into the causal relationships among the BSC perspectives and related factors. Second, it undertakes an empirical investigation for Indian textile SC to develop key managerial insights and provide policy-related recommendations.

scholarly journals A Novel Approach for Optimizing the Supply Chain: A Heuristic-Based Hybrid Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-24
Author(s):  
Yasemin Kocaoglu ◽  
Emre Cakmak ◽  
Batuhan Kocaoglu ◽  
Alev Taskin Gumus
Keyword(s):  
Supply Chain ◽  
Distribution System ◽  
Hybrid Algorithm ◽  
Minimum Cost ◽  
Computational Time ◽  
Strategy Selection ◽  
Distribution Strategy ◽  
Network Problem ◽  
Milk Run ◽  
Delivery Network

Managing the distribution of goods is a vital operation for many companies. A successful distribution system requires an effective distribution strategy selection and optimum route planning at the right time and minimum cost. Furthermore, customer’s demand and location can vary from order to order. In this situation, a mixed delivery system is a good solution for it and allows the use of different strategies together to decrease delivery costs. Although the “distribution strategy selection” is a critical issue for companies, there are only a few studies that focus on the mixed delivery network problem. There is a need to propose an efficient solution for the mixed delivery problem to guide researchers and practitioners. This paper develops a new “modified” savings-based genetic algorithm which is named “distribution strategy selection and vehicle routing hybrid algorithm (DSSVRHA).” Our new algorithm aims to contribute to the literature a new hybrid solution to solve a mixed delivery network problem that includes three delivery modes: “direct shipment,” “milk run,” and “cross-docking” efficiently. It decides the appropriate distribution strategy and also optimal routes using a heterogeneous fleet of vehicles at minimum cost. The results of the hybrid algorithm are compared with the results of the optimization model. And the performance of the hybrid algorithm is validated with statistical analysis. The computational results reveal that our developed algorithm provides a good solution for reducing the supply chain distribution costs and computational time.

Multi-period demand allocation among supplier in a supply chain

2015 ◽  
Vol 10 (2) ◽  
pp. 138-157 ◽  
Author(s):  
Amol Singh
Keyword(s):  
Supply Chain ◽  
Set Theory ◽  
Hybrid Algorithm ◽  
Raw Materials ◽  
Research Work ◽  
Business Environment ◽  
Content Type ◽  
Linear Integer Programming ◽  
Order Preference ◽  
Demand Allocation

Purpose – This paper aims to address the problem of optimal allocation of demand of items among candidate suppliers to maximize the purchase value of items. The purchase value of the items directly relates to cost and quality of raw materials purchased from the supplier. In an increasingly competitive environment, firms are paying more attention to selecting the right suppliers for procurement of raw materials and component parts for their products. The present research work focuses on this issue of supply chain management. Design/methodology/approach – This present research work devises a hybrid algorithm for multi-period demand allocation among the suppliers. The customer demand is allocated by using a hybrid algorithm based on the technique for order preference by similarity to ideal solution (TOPSIS), fuzzy set theory and the mixed linear integer programming (MILP) approaches. Findings – The supply chain network is witnessing a changing business environment due to government policies aimed at promoting new small manufacturing enterprises (small and medium-sized enterprises) for intermediate parts and components. Hence, the managers have an option to select a new group of suppliers and allocate the optimal multi-period demand among the new group of suppliers to maximize their purchase value. In this context, the proposed hybrid model would be beneficial for the managers to operate their supply chain effectively and efficiently. The present research work will be helpful for the managers who are interested to reconfigure their supply chain under the failure of any supply chain partner or in a changing business environment. The model provides flexibility to the managers for evaluation of the different available alternatives to take a decision of optimal demand allocation among the suppliers. The proposed hybrid (fuzzy, TOPSIS and MILP) model provides more objective information for supplier evaluation and demand allocation among suppliers in a supply chain. The managers can use the proposed model to the analysis of other management decision-making problems. Originality/value – This present research work devises a hybrid algorithm for multi-period demand allocation among the suppliers. This hybrid algorithm prioritizes the suppliers and then allocates the multi-period demand among the suppliers. The customer demand is allocated by using a hybrid algorithm based on the technique for order preference by similarity to ideal solution (TOPSIS), fuzzy set theory and the mixed linear integer programming (MILP) approaches.

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