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In recent years, governmental regulations and the pressure of non-governmental organizations have convinced corporations to consider sustainable issues in their decisions. A simultaneous design of forward and reverse logistics can keep us away from sub-optimality caused by tackling these two phases (forward and reverse logistics) separately.

Hence, this paper presents a new multi-objective mathematical model for integrated forward and reverse logistics regarding economic, environmental and social issues. A new hybrid multi-objective metaheuristic algorithm is developed to obtain a set of efficient solutions (Pareto solutions). The proposed algorithm hybridizes a well-known, non-dominated genetic algorithm (NSGA-II) with a simulated annealing algorithm.

To validate the algorithm, its results are compared to the obtained solutions from simple NSGA-II with respect to some comparison metrics. The numerical results show the efficiency of the proposed algorithm. Finally, concluding remarks and future research directions are provided.

By applying a model presented in this paper, one can reach to sustainable and integrated logistics network which considers forward and reverse flow of commodities simultaneously.

There is significant potential for adding value by involving customer in the design process and delivery of logistic services. In order to add value to the overall logistic system, the purpose of this paper is to apply an integrated systems approach for the design of forward and reverse logistics services in order to build a self-organising service that can maximise efficiencies and in particular reduce reverse logistics costs.

Two exploratory case studies were conducted in the logistics systems of housing repair and maintenance sector in the UK. Data were collected using semi-structured interviews, observations, and documented evidence.

The findings of the cross-case analysis suggests that systems approach expressed as the Vanguard Method (Seddon, 2008) has a direct impact on enhancing forward logistics performance and reducing reverse product flows by nourishing three dimensions for learning from demand-driven analysis; capturing customer clean information, demand predictability and categorisation, and failure demand analysis.

Findings from exploratory case studies cannot be easily generalised. Hence, further case studies are needed to enrich the findings, and to facilitate their industrial applications. Further, the paper explores the utilisation of the Vanguard Method only in the area of housing repairs and maintenance logistics services. It would be valuable for future studies to further investigate the utilisation of the Vanguard Method in other logistics services settings.

The paper demonstrates an important dynamics of how logistics services can incorporate customer demands into the logistics design process.

In a quest to meet increasing pressure to incorporate environmental and sustainability factors due to the legislations and growing public awareness, companies are rethinking of strategizing their supply chain network to take control of the reverse flow of products as well. This growing interest has also led to tremendous growth in publications occurring in several reputed journals in the last few years. In this context, the purpose of this article is to perform a systematic literature survey of recent and state-of-the-art papers in order to draw insights and highlight the future directions.

This paper has selected and reviewed 204 papers published from the year 2002–2017. The papers were collected from the web of science and Google scholar database which have the DOI number. The selected papers were then categorized into main five core areas of RSC management namely reverse supply chain (RSC), Reverse Logistics (RL), Remanufacturing, Closed-Loop Supply Chain (CLSC) and Product Recovery Systems (PRS) and then analyzed with great detail. Finally, the research gaps that were identified from the study have been highlighted for future research opportunities.

This paper would serve as a roadmap to the managers who wish to align their forward and reverse supply chains for overall growth and development. It provides an in-depth knowledge on RSC to the researchers working in this domain. The scholars would be able to identify the areas of RSC which have been already addressed and the areas which remain unaddressed.

This paper presents a systematic literature survey of state-of-the-art papers that was published in the reputed journal in the area of RSC. Total 204 numbers of papers which were published in the reputed journals between 2002 and 2017 are reviewed, categorized and analysed to draw the opportunities and future research direction in the area of RSC.

This paper compares the characteristics of reverse logistics in the publishing industry among China, Hong Kong, and Taiwan.

A multiple‐case approach in combination with EIQ (entry of order, items, and quantity) analysis is selected to allow analytical generalization of the findings.

The research findings show that the reverse logistics of Chinese publications is still in early stage and is not mature enough to be interconnected in China, Hong Kong, and Taiwan. The reverse logistics cost in these areas is unlikely to be significantly reduced in the near future.

Instead of making effort to process returned goods, logistics firms or publishers may consider discarding the returned goods directly. The loss on material cost is far less than the manpower spent on processing. Also, publishers can sort returned goods in off‐peak season to save cost on reverse logistics.

This research provides the first empirical study by applying EIQ analysis to understand the challenges of reverse logistics in the publishing industry in China, Taiwan, and Hong Kong, which has been rarely discussed in the past.

Environmental issues have become an important concern in modern supply chain management. The structure of closed-loop supply chain (CLSC) networks, which considers both forward and reverse logistics, can greatly improve the utilization of materials and enhance the performance of the supply chain in coping with environmental impacts and cost control.

A biobjective mixed-integer programming model is developed to achieve the balance between environmental impact control and operational cost reduction. Various factors regarding the capacity level and the environmental level of facilities are incorporated in this study. The scenario-based method and the Epsilon method are employed to solve the stochastic programming model under uncertain demand.

The proposed stochastic mixed-integer programming (MIP) model is an effective way of formulating and solving the CLSC network design problem. The reliability and precision of the Epsilon method are verified based on the numerical experiments. Conversion efficiency calculation can achieve the trade-off between cost control and CO₂ emissions. Managers should pay more attention to activities about facility operation. These nodes might be the main factors of costs and environmental impacts in the CLSC network. Both costs and CO₂ emissions are influenced by return rate especially costs. Managers should be discreet in coping with cost control for CO₂ emissions barely affected by return rate. It is advisable to convert the double target into a single target by the idea of “Efficiency of CO₂ Emissions Control Reduction.” It can provide managers with a way to double-target conversion.

We proposed a biobjective optimization problem in the CLSC network considering environmental impact control and operational cost reduction. The scenario-based method and the Epsilon method are employed to solve the mixed-integer programming model under uncertain demand.

The purpose of this paper is to develop a mathematical model for the network design of a reverse supply chain in a multi-product, multi-period environment. The emission cost due to transportation activities is incorporated into the model to reduce the total cost of emission and study the significance of inclusion of emission cost on the network design decisions.

Mixed integer linear programming formulation is used to model the network. The developed model is solved and analysed using the commercial solver LINGO.

The mathematical model provides a unified design of the network for the entire planning horizon comprising of different periods. A reduction in the total cost of emission is achieved. The analysis of the problem environment shows that the network design decisions significantly vary with the consideration of emission cost.

A single mode of transportation is considered in this study. Also, a single type of vehicle is considered for the transportation purpose.

The developed model can aid the decision makers in making better decisions while reducing the total emission cost. The quantification of the emission cost due to transportation activities is presented in an Indian context and can be used for future studies.

An all-encompassing approach for the design of reverse logistics networks with explicit consideration of product structure and emission cost.

Nowadays, climate change and environmental pollution have become major international concerns, in which logistics and manufacturing activities are playing the major role. In the past decade, more attention has been directed toward environmental issues than ever before. The Paris agreement is one of the most recent milestones in this regard. Due to local and international legislation, managers are highly encouraged to seek out sustainable innovations and strategies to reduce the negative impacts of their business activities. An array of academic and practical activities has been formed around the greening of the supply chain (SC). This paper attempts to review and classify green supply chain management (GSCM) disciplines and best practices from a practical point of view. The authors also investigate the different areas of application and review the GSCM practices in some well-known companies. On this basis, the paper disclose the superiority of Apple company over the other studied cases in applying green practices, particularly in the manufacturing and design areas, while the parcel delivery company has been quite active in the green transportation and green marketing. It is also shown that all of the reviewed cases have been successful in implementing green logistics initiatives thus far.

The cross-docking strategy has a significant influence on supply chain and logistics efficiency. This paper aims to investigate the most suitable and efficient way to schedule the transfer of logistics activities and present a meta-heuristic method of the truck scheduling problem in cross-docking logistics. A truck scheduling problem with products time window is investigated with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks.

This research proposed a meta-heuristic method for the truck scheduling problem with products time window. To solve the problem, a lower bound of the problem is built through a novel two-stage Lagrangian relaxation problem and on account of the NP-hard nature of the truck scheduling problem, the novel red deer algorithm with the mechanism of the heuristic oscillating local search algorithm, as well as adaptive memory programming was proposed to overcome the inferior capability of the original red deer algorithm in the aspect of local search and run time.

Theory analysis and simulation experiments on an industrial case of a cross-docking center with a product’s time window are conducted in this paper. Satisfactory results show that the performance of the red deer algorithm is enhanced due to the mechanism of heuristic oscillating local search algorithm and adaptive memory programming and the proposed method efficiently solves the real-world size case of truck scheduling problems in cross-docking with product time window.

The consideration of products time window has very realistic significance in different logistics applications such as cold-chain logistics and pharmaceutical supply chain. Furthermore, the novel adaptive memory red deer algorithm could be modified and applied to other complex optimization scheduling problems such as scheduling problems considering energy-efficiency or other logistics strategies.

For the first time in the truck scheduling problem with the cross-docking strategy, the product’s time window is considered. Furthermore, a mathematical model with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks is developed. To solve the proposed problem, a novel adaptive memory red deer algorithm with the mechanism of heuristic oscillating local search algorithm was proposed to overcome the inferior capability of genetic algorithm in the aspect of local search and run time.

Supply chain management (SCM) focuses smart logistics and quality service. Diverse elements such as design, procurement, production and sale policies are the keys to SCM efficiency. Due to worsening environmental pollution in recent years, many businesses, government agencies and consumers have become more aware of greenhouse gases (GHG) emissions. In response, the government has established new environmental regulations to control various GHG, such as CO₂ and sulfur dioxide. Therefore, to reduce pollution and its adverse effects, the authors have promoted environmental concerns by developing environmental friendly policies. The purpose of this paper is to develop a multi-objective decision making model that integrates both forward and reverse logistics to determine how best to incorporate recycling and reduce manufacturing costs.

In this study, the authors developed a multi-objective decision-making model that integrates both forward and reverse logistics to determine how best to incorporate recycling and reduce manufacturing costs. They used the normalized normal constraint method as proposed by Messac et al. (2003) to generate a series of uniform lines on a Pareto Frontier chart.

Based on the results of this study, the authors can determine the trade-off between costs and emissions and design the most environmental-friendly and economical strategy for production.

This study is limited to a case study on paper manufacturing.

The authors considered the full truckload discount policy in which buyers can reduce their purchase costs by increasing the number of full truckload product orders; this will reduce transportation costs and also minimize overall carbon emissions.

This study encourages industries to focus on environmental friend policies and social responsibilities.

The authors investigated the impacts of the paper making industry on economy and environment. An increase in demand will negatively impact the environment by causing CO₂ emissions to increase from higher production and the felling of more trees to provide raw materials for manufacturers (paper mills).

The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and logistics operations. The modeling approach adopted aims at the embedding supply chain risks in a closed-loop supply chain (CLSC) network design process and suggests optimal supply chain configuration and risk mitigation strategies.

The method proposes a closed-loop supply chain network and identifies the network parameter and variables required for closing the loop. Mixed-integer-linear-programming-based mathematical modeling approach is used to formulate the research problem. The solutions and test results are obtained from CPLEX solver.

The outcomes of the proposed model were demonstrated through a case study conducted in an Indian hospital furniture manufacturing firm. The modern supply chain is mapped to make it closed loop, and potential risks in its supply chain are identified. The supply chain network of the firm is redesigned through embedding risk in the modeling process. It was found that companies can be in great profit if they follow closed-loop practices and simultaneously keep a check on risks as well. The cost of making the supply chain risk averse was found to be insignificant.

Although the study was conducted in a practical case situation, the obtained results are not indiscriminate to the other circumstances. However, the approach followed and proposed methodology can be applied to many industries once a firm decides to redesign its supply chain for closing its loop or model under risks.

By using the identified CLSC parameters and applying the proposed network design methodology, a firm can design/redesign their supply chain network to counter the risk and accordingly come up with planned mitigation strategies to achieve a certain degree of robustness.