Developing a Fuzzy Green Supply Chain Management Problem Considering Location Allocation Routing Problem: Hybrid Meta-Heuristic Approach

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 mesurement (EVM) and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multi-objective 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.

Green construction supply chain management: Integrating governmental intervention and public–private partnerships through ecological modernisation

In this paper, a supply chain network (SCN) model which simultaneously considers the disruption risks of facility and route is proposed. As most of conventional studies have focused either on facility disruption solely or on route disruption solely, simultaneously considering the disruption risks of facility and route in the SCN model can reinforce the efficiency and stability for its implementation. The SCN model with the disruption risks is formulated as a nonlinear 0–1 integer programming model, and a hybrid metaheuristic (pGA-VNS) approach which combines genetic algorithm (GA) with variable neighborhood search (VNS) is used for solving the nonlinear 0–1 integer programming model. In numerical experiment, various-sized SCN models with the disruption risks at each stage are presented and they are used for comparing the performance of the pGA-VNS approach with those of some conventional approaches (GA and VNS as single metaheuristic approaches and various GA-VNSs as hybrid metaheuristic approaches). Experimental results show that the pGA-VNS approach outperforms conventional GA, VNS and GA-VNS approaches, and the efficiency and stability of the SCN model with the disruption risks are also proved.

Article history: Received April 2, 2016 Received in revised format June 12, 2016 Accepted July 2 2016 Available online July 4 2016 Due to environmental issues, social concerns, increased pollution and enforced regulations; organizations are focusing to include green practices in their supply chain. This can be accomplished by adoption of green supply chain management (GSCM) practices. Therefore, GSCM is now a proactive approach for firms to increase their ecological performance, corporate image, achieve competitive advantages and sustainable business practices. This study identifies, evaluate and analyze the critical factors (CFs) for successful implementation of GSCM practices. The proposed study uses hybrid Fuzzy DEMATEL model to prioritize the identified critical success factors (CSFs) for GSCM adoption. Fuzzy approach is integrated with DEMATEL to deal with uncertainty arises in decision making process. To demonstrate the application of the proposed approach a case study from electronic industry is considered. This approach investigates the cause and effect relationships among the CFs for successful adoption of GSCM practices in Indian electronic organizations. Growing Science Ltd. All rights reserved. 7 © 201

This paper established a three-level supply chain composed of plants, distribution centers, and retailers, and studied the location of distribution centers in the supply chain network and the carbon emissions during processing and transportation. In a random and fuzzy environment, the research objective is to minimize the supply chain’s cost and carbon emission. The multi-objective uncertain equilibrium model of the green supply chain network is established by introducing opportunity constraints, and the stability of the model can be enhanced by using variance function and risk function. Then this research integrated the theory of stochastic programming and fuzzy mathematical programming and employed Monte Carlo simulation; the sample mean approximation, chance-constrained programming and fuzzy expectation to deal with the random parameters and fuzzy parameters in the model so that the uncertain model is clarified. Further, the authors used the hierarchical method, the weighted ideal point method, restriction method, and weighted ideal point method to solve the multi-objective model. Finally, a numerical example is provided to demonstrate the feasibility of the model.

Performance evaluation of green supply chain management using integrated fuzzy multi-criteria decision making techniques

Green Supply Chain Management (GSCM) strives to decrease, if not eliminate, supply chain operations' negative environmental effects. Multi-criteria decision-making (MCDM) strategies should be utilized to evaluate suppliers' GSCM performance because GSCM includes multi-dimensional methods. To address complex and confounding multi-attribute questions in a fuzzy environment, it is essential to devise fuzzy group decision making techniques. The present work introduces a methodology for evaluating the performance of firms in Green Supply Chain Management (GSCM) with regards to green design, green image, green transformation, green logistics, and green management system. This approach relies on integrated fuzzy MCDM techniques. The fuzzy DEMATEL approach is used to calculate the cause and effect corelation between GSCM dimensions. Based on this association, the fuzzy AHP technique is utilized to generate the weights of the relevant criterion. Finally, the fuzzy VIKOR technique is used to evaluate and rank the GSCM performance of alternative suppliers or organizations using the weights obtained from the fuzzy AHP method.

Improvement of Fuzzy Classification Systems Using Metaheuristic (PSO and ICA) with Dynamic Parameter Adaptation in Fuzzy Environment

The rapid development of technology has enabled companies to integrate internal and external partners working together in the supply chain network. Supply chain integration allows fast information to facilitate real-time and reliable decision-making. This study investigates the role of supply chain integration on firm performance through adopting lean manufacturing, green supply chain management, and risk management. The study surveyed manufacturing companies implementing ISO 14000 to represent green supply chain management and integrated information technology as a form of integration. The questionnaires were distributed using a Google form, and 93 valid responses were obtained. Data analysis employed a partial least square approach with SmartPLS software 4.1 version. The data processing results found that supply chain integration increased lean manufacturing by 0.684, green supply chain management by 0.451, and supply chain risk management by 0.333. Lean manufacturing companies using a continuous process control system and process improvements significantly improve green supply chain management by a path coefficient of 0.477, supply chain risk management by 0.206, and firm performance by 0.370. Green supply chain management significantly impacts supply chain risk management by a coefficient of 0.416 and firm performance by 0.189. Supply chain risk management with a system for detecting operational process risks and emergency procedures in overcoming changes in customer orders affects the increase in firm performance by 0.354. The practical contribution of research provides insight for practitioners to invest in information technology and adopt ISO 14000 implementation. Theoretical contributions in developing resources-based view theory in adopting green supply chain management and lean manufacturing.

Nowadays, Economic systems play an important role in environment's field. Along with the rapid change in global manufacturing scenario, environmental and social issues are becoming more important in managing any business. Increasing pressures and challenges to improve economic and environmental performance have been caused developing countries in generally in particular to consider and to start implementing green supply chain management. Green Supply Chain Network Design and Management are an approach to improve performance of the process and products according to the requirements of the environmental regulations. It is emerging as an important approach which not only reduces environmental issues but also brings economic benefit to manufacturers. Green Supply Chain Management (GSCM) has a significant influence to reduce environment's risks. Choosing the suitable supplier is a key strategic decision for productions and logistics management on the supply chain management. The purpose of this study is to describe the GSCM, to determine the allocation of products between plants, collection centers as well as effect of GSCM to the system's cost is investigated. In this paper, GSCM with multiple and conflicting objectives such as reducing costs, increasing customer's level of service and increased flexibility (accountability), respectively by providing mathematical model for optimal allocation of manufacturing products to market demand. In the event of a problem return them to factory pays the collection centers. Also, Green Supply Chain Network Design that includes several manufacturing plants, collection centers, and production with the aim of minimizing the total cost of the chain to be considered.

Due to the expansion of the economy and society, higher standards have been proposed for the growth of enterprises. More and more attention has been paid to the sustainable development of enterprises. The shortage of resources and environmental pollution are another challenge for manufacturing enterprises, requiring businesses to give environmental issues more consideration modern management practices such as green supply chain management take the entire supply chain into account when making decisions. It incorporates suppliers, manufactures, sellers and users and is based on the principle of green manufacturing and supply chain management technologies. Its goal is to reduce environmental impact of the entire process of purchasing, processing, packing, storing, moving, using, and discarding products. This article begins with the meaning of supply chain management, examines the fundamental components of a green supply chain, elaborates on the implementation of a green supply chain, discusses the challenges a green supply chain faces in China, and then proposes green supply chain management strategies.

In the emerging supply chain environment, green supply chain risk management plays a significant role more than ever. Risk is an inherent uncertainty and has a tendency to disrupt the typical green supply chain management (GSCM) operations and eventually reduce the success rate of industries. In order to mitigate the consequences, a fuzzy multi-criteria group decision making modeling (FMCGDM) which could evaluate the potential risks in the context of (GSCM) is needed from the industrial point of view. Therefore, this research proposes a combined fuzzy analytical hierarchy process (AHP) to calculate the weight of each risk criterion and sub-criterion and technique for order performance by similarity to ideal solution (TOPSIS) methodology to rank and assess the risks associated with implementation of (GSCM) practices under the fuzzy environment. The proposed fuzzy risk-oriented evaluation model is applied to a practical case of textile manufacturing industry. Finally, the proposed model helps the researchers and practitioners to understand the importance of conducting appropriate risk assessment when implementing green supply chain initiatives.

Green Supply Chain Management (GSCM) strives to decrease, if not eliminate, supply chain operations' negative environmental effects.Multi-criteria decision-making (MCDM) strategies should be utilized to evaluate suppliers' GSCM performance because GSCM includes multi-dimensional methods. In order to supply solutions to perplexing and demanding multi-attribute inquiries in a fuzzy environment, fuzzy group decision-making procedures must be produced. Based on integrated fuzzy MCDM methodologies, this research provides a methodology for assessing the GSCM performance of firms in terms of green design, green image, green transformation, green logistics, and green management system. The fuzzy DEMATEL technique is used to calculate the cause and effect relationships between GSCM dimensions. Based on this association, the fuzzy AHP approach is utilized to generate the weights of the relevant criterion.

With the increasingly serious global environmental problems, green supply chain management has gradually become an important strategy for enterprise sustainable development and environmental protection. Especially in the electronic information manufacturing industry, the implementation of green electronic supply chain management is of great significance to reducing resource consumption, reducing environmental pollution and enhancing the competitiveness of enterprises. This paper aims to analyze the current situation of green electronic supply chain management, discuss its development trend, and put forward the optimization path and strategy of green electronic supply chain management in the future through typical cases at home and abroad. It is concluded that although some achievements have been made in green electronic supply chain management, it still faces many challenges. Enterprises should take the initiative to assume the corresponding social responsibilities. In the future, with the further improvement of regulations and standards, and the continuous improvement of the information and intelligence level, the green electronic supply chain management will bring a broader development prospect.

This chapter aims to explain the overview of Green Supply Chain Management (GSCM); the significant activities of GSCM; GSCM and collaboration; GSCM and environmental management; GSCM in small and medium-sized enterprises (SMEs); and the multifaceted applications of GSCM. Green supply chain is capable of increasing corporate value while considering its impacts on all processes of physical distribution, production, and environment. Managing a green supply chain is about finding the balance between economic and environmental benefits in global supply chain. GSCM recognizes the disproportionate environmental impact of supply chain processes in an organization. GSCM practices can manifest themselves from the process of selecting raw material to final consumption based on the aspects of reduction, reuse, recycling, and recovery. The chapter argues that the multifaceted applications of GSCM have the potential to enhance organizational performance and gain sustainable competitive advantage in global supply chain.