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The manufacturing industry has evolved with the emergence of cloud computing, leading to the development of cloud manufacturing — a customer-oriented paradigm. The integration of scheduling and logistics in cloud manufacturing is paramount and distinguishes it from traditional manufacturing. Tasks can have three different structures, so this study presents three models that integrate scheduling and logistics for tasks with sequential, parallel, and loop structures, respectively. These models aim to minimize the total cost of the manufacturing system, which includes the implementation cost of subtasks, logistical services cost among factories in different geographical locations, logistical services cost for delivery of the order (task) to the customers, and the earliness/tardiness cost of orders. The numerical examples in small and medium sizes are solved using the CPLEX solver in the GAMS software. However, due to the high complexity of the models presented, a genetic algorithm is developed to solve large examples. To showcase the significance of the main features of the proposed models, two comparable models are employed, each with one feature removed. In addition to the factors that are considered to get the models close to reality, a sensitivity analysis is conducted to design effective guidelines for cloud manufacturing managers.

The purpose of this study was to explore the characteristics of logistics networks that facilitate effective coordination by third-party logistics (3PL) enterprises. Utilizing a comprehensive literature review to bridge the existing research gap, this study meticulously examined the relationships between specific keywords within the SCOPUS database through the use of the VOSviewer tool. This preliminary investigation revealed theoretical deficiencies regarding the operations of 3PL enterprises and the concepts of network and logistic coordination, prompting a detailed empirical analysis of 69 networks where 3PL logistics operators were engaged. This analysis was informed by quantitative data collected from these networks, alongside insights from interviews with experts who assessed the performance of the logistics operators and their clients. The research highlighted particular network attributes, derived from logistic coordination mechanisms, that strongly correlate with the sophisticated use of such mechanisms by operators. One significant limitation of this research was its narrow focus on correlation and the examination of traditional network coordination mechanisms. Nevertheless, the outcomes of this study offer valuable insights for both scholars, aiming to refine the theoretical underpinnings of logistic and network coordination and practitioners within the logistics sector. These findings enhance our comprehension of the dynamics influencing logistic coordination’s effectiveness across diverse settings and elucidate the logistics network characteristics that promote successful collaboration among network members and throughout the supply chain.

We examine the robustness of centralized, landbound relief operations' capability to promptly reach areas affected by a disaster event from a network perspective. We initially look at two idealized road networks: a two-dimensional grid and a scale-free network, and compare them to an actual road network obtained from OpenStreetMap. We show that, from a node designated as the center for relief operations (a "relief center"), damage to a road network causes a substantial fraction of the other nodes (about 20% in the three networks we examined) to become initially inaccessible from any relief effort, although the remaining majority can still be reached readily. Furthermore, we show the presence of a threshold in the two idealized road networks but not in the real one. Below this threshold, all nodes can robustly be reached in a short span of time, and above it, not only the partitioning mentioned above sets in, but also the time needed to reach the nodes becomes susceptible to the amount of damage sustained by the road network. Under damage sustained by random segments of the network, this threshold is higher in the scale-free network compared to the grid, due to the robustness of the former against random attacks. Our results may be of importance in formulating contingency plans for the logistics of disaster relief operations.

Home delivery service is one of the most important cost drivers in e-commerce industry. We consider the three-dimensional container packing problem under home delivery service, where each rectangular item with its specific destination is loaded orthogonally onto a rectangular container so that the utilization rate of the container space is maximized. In our framework, we assume the routing of a consignment to be given, which turns out that there is an order of unloading items with respect to the consignment. If we load items without considering the order of unloading items, we may unload and reload other unconcerned items drastically while unloading the required item. Therefore, in this paper, the unloading costs for a consignment are precisely defined according to the invisible and untouchable rule, and a subvolume scheme based algorithm is proposed. Our experimental results suggest our approach to be promising.

One of the most important operational management problems of a cross docking system is the truck scheduling problem. Cross docking is a logistics management concept in which products delivered to a distribution center by inbound trucks are immediately sorted out, routed and loaded into outbound trucks for delivery to customers. The truck scheduling problem in a multi-door cross docking system considered in this paper comprises the assignment of trucks to dock doors and the determination of docking sequences for all inbound and outbound trucks in order to minimize the total operation time. A mathematical model for optimal solution is derived, and the genetic algorithms (GAs) and the adaptive genetic algorithms (AGAs) as solution approaches with different types of chromosomes are proposed. The performance of the meta-heuristic algorithms are evaluated using randomly generated several examples.

The manager is responsible for the operations of a distribution center (DC) and multiple retail outlets selling a seasonal product. Initially, the DC keeps the inventory, which is allocated to the outlets in the season. There are inventory holding costs at the DC and the outlets; variable shipment cost for transferring inventory from the DC; fixed ordering cost and shortage cost at an outlet. Exact demand at each outlet is a decreasing function of price. To maximize the expected profit of the season, the manager needs to determine the markdown prices for retail outlets and quantity of inventory allocated to them. The problem can be modeled as a dynamic program (DP) which takes too heavy computational effort to solve. We develop a DP-based heuristic for solving the problem. The heuristic takes light computational effort and yet has good accuracy. Insights streamlining the markdown operations are deduced from the numerical results.

This paper presents a group decision-making model using a distance aggregator based on Ordered Weighted Distance (OWD) which offers a solution that can reduce disagreement between decision makers (DMs). This paper discusses decision rules and sets out measures to evaluate compensatory effects that have a bearing on DMs’ opinions. The model uses formulations of distances to reveal the differences in opinion among DMs and discusses the meanings of distance and the information presented by each DM. Finally, a case study of a logistics problem is used to illustrate how the model is applied.

The total size of the edible oils market in India was estimated to be 13 million tons (mt) out of which imports amounted to about 4 mt. This made India the largest importer of edible oils in the world. Various edible oils are consumed in the India depending on the regional tastes and preferences. A differential in the duties on oil seed and oils made it favorable to import edible oils instead of oilseeds. Similarly, a differential duty between the refined oil and the raw oil encouraged the import of raw oil in order to support the domestic refineries.

Adani Wilmar Limited (AWL) was a part of the Adani group, which started as a trading company mainly into exports of commodities. The group had recently entered into the infrastructure sector with the building of the Mundra port. The group had formed a joint venture with Wilmar Trading of Singapore to enter into the edible oil business. The company was setting up a re.nery with capacity of 600 tons per day. It planned to sell half of the production as bulk oil and the rest as packed oil. The company viewed supply chain management as one of the important means to get a competitive edge. Approximately 70% of the total logistics cost was accounted for by transportation cost. Some of the key decisions the company faced was the location of the warehouses, mode choice and routing.

TNT Launches Clinical Express.

In order to improve the efficiency of the e-commerce logistics system, this paper analyzes the application of dynamic bandwidth resource allocation algorithm in intelligent logistics tracking scenarios and distribution scenarios, and achieves the purpose of optimizing the allocation of bandwidth resources by changing the sampling rate of the control signal. Moreover, this paper designs and implements an e-commerce logistics information system based on the Internet of Things, and starts with each functional module to introduce in detail the various functions realized by the system in this paper. This paper changes the traditional logistics operation mode, through the realization of various functional modules, users can grasp personal historical orders and view the list of historical orders. Finally, this paper analyzes the performance of this system through experimental research. The results of the research show that the e-commerce logistics system based on the Internet of Things proposed in this paper is effective.

The growth of world population, limitation of resources, economic problems, and environmental issues force engineers to develop increasingly efficient solutions for logistic systems. Pure optimization for efficiency, however, has often led to technical solutions that are vulnerable to variations in supply and demand, and to perturbations. In contrast, nature already provides a large variety of efficient, flexible, and robust logistic solutions. Can we utilize biological principles to design systems, which can flexibly adapt to hardly predictable, fluctuating conditions? We propose a bio-inspired "BioLogistics" approach to deduce dynamic organization processes and principles of adaptive self-control from biological systems, and to transfer them to man-made logistics (including nanologistics), using principles of modularity, self-assembly, self-organization, and decentralized coordination. Conversely, logistic models can help revealing the logic of biological processes at the systems level.

The Amazon region has the largest hydrographic basin in the world and a favorable geographical location as a strategic export point but does not satisfactorily exploit its potential for transport and cargo flow, mainly as a differential factor of logistic competitiveness. For the waterway mode, cargo transportation is predominantly carried out by pushed convoys. The objective of this research is to evaluate and select, the best river train for the outflow of iron ore on the Marabá – Vila do Conde stretch, through a multiple criteria decision-making approach. To meet the objectives, a methodological framework is proposed using a hybrid AHP-DEMATEL method, based on a statistical analysis and to guarantee the reliability of the results for the proposed alternatives and not only considering the preference function, the ELECTRE method was used and also a parametric comparison of the AHP results. The main goals of this work were achieved and it was possible to infer that the combination of these methods has, in addition to the evident efficacy, a high reliability in the water transport area, being able to be used with accuracy of diverse forms in the academic area, as well as in industrial applications. Therefore, it can be affirmed that the best-pushed convoy configuration for the iron ore runoff in the Marabá – Vila do Conde stretch is composed by six barges in the arrangement of two columns and three rows with the measurements, by barge, with length of 60.96m; beam of 13.75m; and a 5m molded depth.

The increase in e-commerce and omnichannel commerce is having a significant impact on the supply chain sector and its warehouses. Fluctuations in demand and priorities, the requirement for value-added service, government regulations and other factors put pressure on the operational decision makers on the warehouse floor and the systems that support them. The increasing complexity of daily warehouse operations means that decision support systems will need to become more sophisticated and intelligent to assist decision makers in real-time. The aim of this literature review is to investigate how decision support in warehousing and distribution operations is examined in the research literature. The objective of this review is to understand how this decision support research can assist operational decision makers to manage and complete the daily volume of work through the warehouse. Fifty-one articles were obtained by the literature search. Articles were categorized by type of warehouse, decision support target, operational task and problem type, research article methodology, architecture and technology. Decision support is examined in almost all areas of warehousing operations with the use of a variety of methods and technologies within the research literature. Most “daily warehouse operational” decision support deals with expertise transfer and reacting to real-time events. This paper highlights the lack of research into human–machine collaboration in adaptive decision support systems to assist warehouse operational decision makers.

Information sharing is an important factor for effectiveness within the internal supply chain. In this paper we use a methodology for mapping information flows in an internal supply chain, and case studies of two Swedish multinational organisations. Eight retrospective cases were used to map, describe and analyse the information flow that supports the physical material flow from the receipt of an order to point of delivery. Every involved person was interviewed on at least one occasion each. The interviews were conducted to map and describe the information and physical material flow. The aim was to identify factors that could improve and rationalise information flows and generate a better flow within the organisation.

The study shows the importance of an integrated information system, but also clearly indicates the importance of a collaborative culture and an awareness of the human–technology interface. The study also shows that three factors of interface distortions are most frequent in the cases: (1) changes registered in the database trigger no action among the staff, (2) new knowledge to staff is stored only orally and not in the database, and (3) interface between the paper system and the database, and between the old and the new information storage culture.

This research seeks to examine the artificial intelligence (AI) competencies in logistics management by reviewing its capabilities, challenges and benefits. To increase the use of AI in logistics management, this study addresses the issues of the current technology in AI adoption in logistics management. This goal was accomplished using a systematic methodology. First, a detailed review was conducted to look at the advantages, challenges and current AI competencies. Using a survey instrument and a simple random sampling technique, the required data was collected from 44 businesses which effectively use AI in their logistical operations. The collected data gave insightful information on how AI is currently being used in logistics management. The outcome of this study shows that AI significantly affects logistics management. The study reveals notable competencies, significant challenges and major advantages of AI in managing logistics activities through the systematic analysis and synthesis of the obtained data. These findings demonstrate how AI has the potential to improve operational effectiveness, resource allocation, decision-making processes and supply chain operations in logistics management. A potential recommendation is to establish strategies and guidelines for efficient implementation and integration of AI technologies in logistics management based on the observed technology gap and the research’s findings. This will minimise the current gap and optimise the advantages of the industry’s use of AI, resulting in higher performance, cost savings and increased competitiveness for logistics business organisations.

Innovation within logistics organizations does not occur in isolation. Most innovation occurs in response to environmental factors outside the direct control of management. Factors such as the location of the organizations, the available technologies, the accessibility of knowledge and globalization can all have an impact on how a business responds in innovative ways that ensure it can remain competitive. The logistics function is increasing in its strategic importance as more and more firms in developed economies such as Singapore and Australia are forced to complete globally to survive. In such a dynamic environment, logistics business must innovate; and to benefit from innovative technologies, systems, processes and practices they must consider the external contingencies that will have the greatest impact on the business operation. This paper provides important lessons from managers in logistics organisations in Australia and Singapore; and demonstrates how contingent factors can affect how firms differ in their strategies and capacities to innovate.

COVID-19 pandemic has drawn great attention to environmental uncertainty. The current paper attempts to conceptually develop and empirically validate a research framework that explains how the firms’ environmental uncertainty influences their innovation capability and stakeholder value. Drawing on contingency theory, resource dependence theory, and stakeholder theory, this study develops a conceptual framework for the related constructs and employs a partial least squares structural equation modelling (PLS-SEM) to test the suggested framework. The empirical results validate both measurement (outer) and structural (inner) models. They indicate that environmental uncertainty is negatively associated with the innovation capability and stakeholder value while innovation capability is positively related to both internal and external stakeholder value. The results also show that internal stakeholder value positively affects external stakeholder value. Providing valuable insights into logistics and supply chain management, our study contributes to research in environmental uncertainty and innovation management based on the stakeholder theory.

An efficient supply chain is the one which fastens the e-commerce processes to meet customers’ needs and expectations. Managing supply chains in e-commerce involves materials procurement, manufacturing and distribution of the required products to the customers in a timely manner. This process also includes warehousing, inventory tracking, demand and supply management, order entry and order management.

A well-structured and sustainable supply chain can enhance the productivity of e-commerce processes. This chapter presents an approach on how e-commerce is influencing supply chains and logistics. Also it discusses how analytics can be leveraged to improve the last mile delivery in e-commerce platforms.

During the development of socio-economic systems with a certain periodicity, there arise crises initiated by the impact of political, financial, economic, epidemiological, and other nature events. Over the past few years, the global community faced the spreading and destabilizing effects of COVID-19 on all areas of life, business, production, commercial and non-commercial structures, and public administration. The chapter attempts to reveal and interpret current trends in the development of socio-economic and transport and logistics systems within COVID-19, revealing the reasons that characterize the emergence of imbalances in economic and transport and logistics systems. Within the framework of the studied topic, the chapter substantiates the necessity of forming forecast values for the sustainable functioning of supply chains, considering the possibility of interpreting the forecast in several variations. The basis for the formation of forecast values of development in the future is the fact that the value and volume of online commerce are already increasing every year. The unprecedented surge in online sales associated directly with the COVID-19 pandemic has brought volumes closer to the futures indicators of 2025. According to expert opinion, electronic sales have every chance to absorb 80% of the market by 2030. The research used classical methods of scientific knowledge, including system analysis, synthesis, graphical interpretation of the given data, comparative analysis, and abstraction. The summarizing part of the research substantiates the author’s opinion on the formation of areas of sustainable operation of logistics companies in the medium term. It is necessary to invest in the development of IT technologies and transport and storage infrastructure of logistic complexes and form optimal paths of transport processes. Logistics companies that will adhere to these recommendations should make clear scripted forecasts in several development options, considering the emergence of crisis and force majeure situations. One of the conclusions of the research is the fact that competition within the framework of global logistics systems, which has expanded to all levels of their organization up to the local one, determines the main success parameters in today’s business, not only the quality and value of the product but, to a greater extent, the time parameters of logistics services, the rapid development of last-mile logistics, and the optimization of intermodal and multimodal operations.

The development of the export potential of the Southern Federal District of the Russian Federation is associated with the justified need to increase the capacity of transport and logistics infrastructure of the studied region and make more rational use of its geopolitical potential. Using geopolitical potential, regions of the Russian Federation seek to optimize the development of competitive industries in areas of economic activity, expanding export potential and pursuing the objectives of government policy to increase the region’s non-resource and non-energy exports, including from the perspective of the region’s transit potential. In essence, the concepts of export potential and transit potential are interrelated and interdependent; In practice, the formation and development of one provoke the growth of the other. Transit and export potential are concepts based on export-oriented production and on the capacity of transport and logistics infrastructure. Investments in the construction of regional distribution centers, which are embedded in the distribution chains of industries operating in the region, have the greatest importance in developing the transit and export potential of the logistics system. The chapter identifies the need to transition logistics services provided in the Russian Federation to a new integrated level of service. The reason for this situation is the increasing demand for quality and accelerated time performance of services every year, as evidenced by the expansion of the very concept of fulfillment. The authors applied statistical analysis and comparison methods, sampling, correlation and regression, and horizontal and vertical analysis. Investments in the construction of logistics centers are objectively local in practice, i.e., they have a local character. The investor receives the necessary information via the relevant ministries and departments, and the possible benefits and threats in terms of production location and preferences are considered in the investment decision-making process. In this process, the agencies must be fully involved in preparing a package of information on the available transport and logistics options for the transport and marketing of products. Implementing an investment project is a lengthy process. By understanding the investor’s needs, it is possible to offer solutions that are as attractive as possible for the investment. Since the necessary transport and logistics system will be developed by local businesses and logistics operators, the regional economy receives significant benefits realized in the creation of new jobs and increased revenues for the regional budget.