Designing and evaluating sustainable logistics networks

The design of sustainable logistics network under uncertainty

This paper is based on the concept of ‘logistics excellence’. In the first part the parameters that define such excellence in the internationalization process of companies are discussed, with particular attention to its effects on the design of logistics networks. A critical analysis of some Italian case studies of “logistics excellence” is presented, to show how some Italian companies, involved in foreign trade, have changed their network design in order to reach excellent performances. One of the most interesting results of this analysis is that in some cases goals behind decisions were too high (“overperformance”) and generated network designs that were too expensive and complex if set against a balanced needs analysis (of clients and logistics operators). Only those who have borne in mind their clients’ needs as well as the need of limiting network costs and have supported their systems with creative choices have managed to achieve the best results within the Italian logistics system. In the light of these considerations, the second part of the article analyses the logistics situation in commercial relations between Italy and Russia (with specific reference on export from Italy to Russia) and points out how, in the face of some structural problems posed by the logistics distribution in Russia, the network design solutions that can reduce costs the most are those which will turn out being the most suitable in the long run. In the light of this, the steps to be taken in order to support the design of adequate logistics networks connecting Italy and Russia are described; the options offered by intermodal transport when adequately combined with newly designed logistics networks are also highlighted.

Sustainable supply chain network design has attracted great attention of academia and industry in recent years. Baijiu is one of the world’s oldest distilled alcoholic beverages and plays a significant role in Chinese culture and Chinese people’s daily life. As the production and consumption of Baijiu have a significant influence on the economic, environmental, and social performance of supply chain management, sustainable supply chain network design decisions are critical to the long-term success of the industry. In concert with the rapidly growing Chinese economy, there is a growing demand for a sustainable Baijiu industry. Therefore, this paper constructs and optimizes a network decision-support model for a sustainable Baijiu industry network design. To achieve this, the Baijiu supply chain is examined and a model is proposed for a design that encompasses economic (costs), environmental (carbon emissions), and social (local employment and regional per capita GDP) dimensions. R language programming is then applied to solve the model. A case example indicated that S1 was the optimal decision for reducing costs, S2 was the optimal solution for minimizing carbon emissions, and S3 was the best for maximizing the social impact. Considering the situation of the Baijiu industry and the focal enterprise, it was concluded that S1 would be the best solution for the case company. And the results verified the effectiveness of the framework. This paper develops a systematic and effective approach that decision-makers can use to conduct sustainable network design for Baijiu enterprises.

Since the waste electrical and electronic equipment (WEEE) is increased rapidly, the disposition of WEEE has caused tremendous attention in China. The government is drafting regulation which will makes Original Equipment Manufacturers formally responsible for taking back their products. Logistics network design becomes vital for cost efficient managing WEEE in coming day. The aim of this paper is to take a detailed look at logistics network design for WEEE. Firstly, From the point of resource's re-use, Integrated logistics network for WEEE is presented taking into account all problems about reuse of entire products, parts of products, and reclaimed materials decomposed from WEEE. Secondly, a mixed integer programming (MIP) model is presented for designing logistics network of WEEE, its objective is to optimize the logistics network infrastructure of WEEE and minimize the total costs. Finally, an illustration is given through a hypothetical example

To face the new challenges caused by modern industry, logistics operations managers need to focus more on integrating sustainability goals, adapt to unexpected disruptions and find new strategies and models for logistics management. The COVID-19 pandemic has proven that unforeseen fragilities, negatively affecting the supply chain performance, can arise rapidly, and logistics systems may confront unprecedented vulnerabilities regarding network structure disruption and high demand fluctuations. The existing studies on a resilient logistics network design did not sufficiently consider sustainability aspects. In fact, they mainly addressed the independent planning of decision-making problems with economic objectives. To fill this research gap, this paper concentrates on the design of resilient and sustainable logistics networks under epidemic disruption and demand uncertainty. A two-stage stochastic mixed integer programming model is proposed to integrate key decisions of location–allocation, inventory and routing planning. Moreover, epidemic disruptions and demand uncertainty are incorporated through plausible scenarios using a Monte Carlo simulation. In addition, two resiliency strategies, namely, capacity augmentation and logistics collaboration, are included into the basic model in order to improve the resilience and the sustainability of a logistics chain network. Finally, numerical examples are presented to validate the proposed approach, evaluate the performance of the different design models and provide managerial insights. The obtained results show that the integration of two design strategies improves resilience and sustainability.

Environmental pollution and energy shortages have brought about an increased focus on new energy vehicles. Hydrogen fuel cell vehicles (HFCVs) have experienced rapid development due to the potential to alleviate energy pressures and reduce pollution emissions. Near zero-carbon emissions offer a promising avenue for promoting sustainable transportation development. To evaluate the impact of HFCVs on the transportation environment, this paper investigates the problem of sustainable transportation network design including HFCVs. Specifically, the problem is formulated as a bi-level multi-objective programming problem, with the upper level aimed at determining the optimal network design scheme considering multiple objectives, while the lower level addresses the mixed traffic flow that comprises both HFCVs and fuel vehicles. To solve the multi-objective sustainable network design problem, an integrated solution framework that combines the particle swarm optimization (PSO) algorithm with the Frank-Wolfe algorithm (FW) is developed. Specifically, the PSO algorithm is utilized to solve the upper-level model and identify the optimal network design schemes, while FW algorithm is adopted to handle mixed traffic flow assignments. Finally, the proposed model and algorithm are implemented in two numerical experiment to demonstrate their effectiveness and efficiency.

PurposeDue to unceasing declination in environment, sustainable agro-food supply chains have become a topic of concern to business, government organizations and customers. The purpose of this study is to examine a problem associated with sustainable network design in context of Indian agro-food grain supply chain.Design/methodology/approachA mixed integer nonlinear programming (MINLP) model is suggested to apprehend the major complications related with two-echelon food grain supply chain along with sustainability aspects (carbon emissions). Genetic algorithm (GA) and quantum-based genetic algorithm (Q-GA), two meta-heuristic algorithms and LINGO 18 (traditional approach) are employed to establish the vehicle allocation and selection of orders set.FindingsThe model minimizes the total transportation cost and carbon emission tax in gathering food grains from farmers to the hubs and later to the selected demand points (warehouses). The simulated data are adopted to test and validate the suggested model. The computational experiments concede that the performance of LINGO is superior than meta-heuristic algorithms (GA and Q-GA) in terms of solution obtained, but there is trade-off with respect to computational time.Research limitations/implicationsIn literature, inadequate study has been perceived on defining environmental sustainable issues connected with agro-food supply chain from farmer to final distribution centers. A MINLP model has been formulated as practical scenario for central part of India that captures all the major complexities to make the system more efficient. This study is regulated to agro-food Indian industries.Originality/valueThe suggested network design problem is an innovative approach to design distribution systems from farmers to the hubs and later to the selected warehouses. This study considerably assists the organizations to design their distribution network more efficiently.

Logistics network design leads to critical components in supply chain sustainability specifically in the United States since businesses aim to achieve reduced operational expenses together with decreased environmental impact. Since their initial inception as traditional transportation systems, logistics networks have gradually developed into worldwide systems which offer efficiency but cause raised environmental emissions and energy utilisation. The study evaluated the trade-offs between cost efficiency and environmental sustainability in logistics network design, particularly examining how different operational decisions affect both logistics cost and carbon emissions. A primary quantitative approach was adopted by the research, which utilised data obtained from 380 representatives of logistics companies operating in the USA, and a survey questionnaire was utilised. SmartPLS software analysed direct and indirect relationships between independent and dependent variables during the data evaluation process. Sustainable logistics procedures decrease environmental damage, but expenses typically rise in the process. The examination discovered that inventory management, together with sustainability initiatives, create a major influence over carbon emissions and logistics expenses. Transportation mode selection demonstrated better effectiveness in lowering environmental emissions than it did in cutting costs down. The research established that organisations need to find effective ways to achieve financial efficiency while promoting sustainability. Strategic decisions made by companies need to maintain sustainability steps while avoiding competitive setbacks through an understanding that sustainable logistics practices generate lasting advantages. The sustainability of business logistics networks requires top priority while policymakers need to back sustainable logistics programs with both incentives and rules. More research is necessary to determine multiple variables that affect logistics network design.

Truck flow plays a vital role in urban traffic congestion and has a significant influence on cities. In this study, we develop a novel model for solving regional logistics network (RLN) design problems considering the traffic status of the background transportation network. The models determine not only the facility location, initial distribution planning, roadway construction, and expansion decisions but also offer an optimal solution to the logistics network service level and truck-type selections. We first analyze the relationship between the urban transportation network and the RLN design problem using real truck data and traffic flow status in a typical city. Then, we develop the uncover degree function (UDF), which reflects the service degree of the RLN and formulates based on an impedance function. Subsequently, the integrated logistics network design models are proposed. We model the RLN design problem as a minimal cost problem and design double-layer Lagrangian relaxation heuristics algorithms to solve the model problems. Through experiments with data from the six-node problem and Sioux-Falls network, the effectiveness of the models and algorithms is verified. This study contributes to the planning of regional logistics networks while mitigating traffic congestion caused by truck flow.

Logistics network is one of the most important parts of supply chains with significant share in achieving sustainability across them. In this paper, we investigate a new multi-objective mixed integer linear programming model for the design of multimodal logistics network. A bi-objective mathematical model is introduced and two conflicting objectives including the minimization of total cost and the total environmental impact are taken into account. Effective environmental life cycle assessment-based method is incorporated in the model to estimate the relevant environmental impacts. Due to budget constraints, financing decisions for facility construction are considered in the proposed model. To cope with the model objective functions, the augmented ε-constraint method is applied. Computational analysis is also provided by using a cement multimodal rail-road logistics network case study to present the significance of the proposed model. Results show that utilizing the proposed multi-period optimization model influences the location of multimodal terminals and their construction time. Also, the results show that the use of the proposed model enhances the efficiency of terminals. On the other hand, computational results indicate that preferences of decision-makers and the importance of environmental objective have significant impacts on the topology of transportation network.

ABSTRACTWith the concern about environmental issues, supply chain designers and managers need to make trade-offs between the environmental impacts and costs of a logistics network. We develop a multi-objective optimization model that minimizes the total cost and CO2 emissions of a regional timber logistics network and seeks for the simultaneous optimization of logistics network design and operation. The generic model is applied to a case study in Jiangle County in China. The Pareto solution set, derived by applying the normalized normal constraint method, shows the relationship between carbon emissions and total cost. Our results reveal that both network structure and the allocations of timber flows have effects on the Pareto solutions, suggesting the importance of considering network design and management together in logistics network analysis. The model results also indicate that though the current carbon price is hard to trigger the change of the timber logistics network structure in Jiangle County, it can still be a driving force to push the decision-makers to implement lower carbon logistics plans. Additionally, sensitivity analysis shows that improving road conditions can remarkably reduce CO2 emissions in the logistics network and that maintaining an appropriate ratio of timber supply to demand can lead to some compromise between carbon emissions and total cost. These findings offer new insights into the trade-offs between the carbon emissions and total cost of the regional timber logistics network, which are of value to logistics network designers and managers as well as policy-makers in the study region and beyond.

The design of logistics networks is one of the most important areas of application for multicommodity network design models. Logistics networks (or supply chains) connect suppliers, manufacturing plants, warehouses, distribution centers and customers to coordinate the acquisition of raw materials and components, their transformation into finished products and the delivery of these products to the customers. Over the last 40 years, the realism of logistics network design models has greatly improved and efficient solution methods have been developed to solve these models. There is now a vast literature on the topic with a very large number of models addressing the many problem variants encountered in practice. This chapter provides a general modeling framework that can be used to express many of these variants and gives a brief overview of the main solution methodologies. It also discusses two important and recent trends: the treatment of risk and uncertainty in the design of logistics networks and the incorporation of environmental, sustainability and reverse logistics aspects.

Logistics entities are interrelated to each other, any disruption or sudden unavailability of the entities may cause severe cascading disruption effects on the functioning of the entire logistics network. In analyze the cascading disruption effects, it is important to actively concern the normal logistics practices, rather than passively emphasize on learning from the past incidents. This paper proposes a resilience analysis framework for the analysis and design of logistics network on how to help the network to cope with complexity under disruption. Under the resilience analysis framework, the logistics network is modeled as a probabilistic network graph, the resilience can then be analyzed by the reliability of all the independent connection paths among the logistics entities with connection weightings. The design of the logistics network is then further proposed by (1) risk sharing and resilience enhancement by means of the redundancy effect, and (2) restoration and recovery of the network by means of dependency routing. Therefore, this paper can provide an efficient way to analyze and design the stability of the logistics network as well as to understand the ability of the network to return to a stable state after disruptions from failure.

Problem. In the conditions of rapid changes in demand and supply in transportation markets, there is a need for corresponding changes in logistics technologies and networks, which are carried out through their reengineering. Existing mathematical models for the optimization of logistics networks are designed for conditions with point-wise, clearly defined input data, which does not allow obtaining solutions resistant to changes in the external environment. This determined the relevance of the scientific and applied task of developing mathematical models of multi-criteria optimization problems of logistics networks for the conditions of interval submission of input data. Goal. The goal is to increase the efficiency of the logistics network optimization technology at the stage of re-engineering by developing a mathematical model of the multi-criteria optimization problem for the conditions of interval submission of input data. Methodology. According to the results of the decomposition of the problem of system optimization of logistics networks as the most complex defined task of their structural and topological optimization. When developing the model, the methodology of system design of territorially distributed objects, methods of multi-criteria optimization, theories of utility and decision-making were used. The apparatus of interval mathematics was used to compare solution options with vaguely specified input data. The results. The result are the formulated and completed formalization of the task of optimizing logistics networks as territorially distributed objects. The relationship for the objective function and constraints of the optimization task of topological structures of centralized three-level logistics networks is proposed. Originality. A mathematical model of the task of reengineering topological structures of centralized three-level logistics networks according to cost and efficiency indicators for interval defined input data and values of local criteria using comparison indices based on the Hukuhara difference has been developed. Practical value. The obtained results make it possible to increase the reliability of optimization results in the processes of design, development planning and reengineering of logistics networks, to obtain variants of the construction of their topological structures that are resistant to changes in external conditions.

This paper describes the approach and first results of current research performed at the Telematics Research Centre (TRC) which focusses on a systematic approach to the analysis and (re)design of logistic networks. In this research, telematics is seen as a supporting technology enabling logistic network improvement.The first part of the research aims at developing a reference model allowing the investigation of the application of telematics in logistics. This model uses a functional perspective: organisations carry out several functional processes. Insight in these processes and their interactions as well as in the possible telematics services and their interactions is necessary in order to successfully develop telematics applications for logistics.In the second part, a method is developed for supporting the judgement of the technical, economic, and social aspects of the introduction of telematics, both quantitatively and qualitatively.KeywordsFeasibility studylogisticsnetworksprocessesprocess redesignquantitative and qualitative factorsreference modelstelematics.