Logistics Operations Research Articles

Institutional Strengthening and Improvement of National Logistics Performance Through The Establishment of A National Supply Chain Agency

The logistics sector has a very important role in driving Indonesia's economic growth. However, the national logistics system currently faces various obstacles that prevent it from reaching its full potential. Many challenges slow down the development of this sector. To overcome these obstacles, it is necessary to strengthen institutions that are able to integrate and optimize logistics performance throughout Indonesia. This research suggests the establishment of a National Supply Chain Agency as a solution to improve the coordination, efficiency, and effectiveness of the logistics system. The purpose of this study is to identify and evaluate the role and impact of the establishment of the National Supply Chain Agency on improving national logistics performance. This research uses a qualitative method with data collection from literature studies. The collected data were then analyzed through the stages of filtering, presenting, and drawing conclusions. The results showed that the establishment of the National Supply Chain Agency is an important step to improve logistics performance in Indonesia. The agency is expected to address current challenges, such as inefficiency, high logistics costs, and distribution delays. Thus, the National Supply Chain Agency is proposed as a solution to improve the competitiveness of national logistics, both in the domestic and international markets, and contribute to sustainable economic growth.

Automatic Scheduling Method for Customs Inspection Vehicle Relocation Based on Automotive Electronic Identification and Biometric Recognition

This study presents an innovative automatic scheduling method for the relocation of customs inspection vehicles, leveraging Vehicle Electronic Identification (EVI) and biometric recognition technologies. With the expansion of global trade, customs authorities face increasing pressure to enhance logistics efficiency. Traditional vehicle scheduling often relies on manual processes and simplistic algorithms, resulting in prolonged waiting times and inefficient resource allocation. This research addresses these challenges by integrating EVI and biometric systems into a comprehensive framework aimed at improving vehicle scheduling. The proposed method utilizes genetic algorithms and intelligent optimization techniques to dynamically allocate resources and prioritize vehicle movements based on real-time data. EVI technology facilitates rapid identification of vehicles entering customs facilities, while biometric recognition ensures that only authorized personnel can operate specific vehicles. This dual-layered approach enhances security and streamlines the inspection process, significantly reducing delays. A thorough analysis of the existing literature on customs vehicle scheduling identifies key limitations in current methodologies. The automatic scheduling algorithm is detailed, encompassing vehicle prioritization criteria, dynamic path planning, and real-time driver assignment. The genetic algorithm framework allows for adaptive responses to varying operational conditions. Extensive simulations using real-world data from customs operations validate the effectiveness of the proposed method. Results indicate a significant reduction in vehicle waiting times—up to 30%—and an increase in resource utilization rates by approximately 25%. These findings demonstrate the potential of integrating EVI and biometric technologies to transform customs logistics management. Additionally, a comparison against state-of-the-art scheduling algorithms, such as NSGA-II and MOEA/D, reveals superior efficiency and adaptability. This research not only addresses pressing challenges faced by customs authorities but also contributes to optimizing logistics operations more broadly. In conclusion, the automatic scheduling method presented represents a significant advancement in customs logistics, providing a robust solution for managing complex vehicle scheduling scenarios. Future research directions will focus on refining the algorithm to handle peak traffic periods and exploring predictive analytics for enhanced scheduling optimization. Advancements in the intersection of technology and logistics aim to support more efficient and secure customs operations globally.

Supply Chain Management in Smart City Manufacturing Clusters: An Alternative Approach to Urban Freight Mobility with Electric Vehicles

The development of green production types such as personalized production and shared manufacturing, which use additive technologies in city multifloor manufacturing clusters (CMFMCs), has led to an increase in last-mile parcel delivery (LMPD) activity. This study investigates the integration of electric vehicles and crowdshipping systems into smart CMMCs to improve urban logistics operations related to the distribution of products to consumers. The aim of this study is to improve the LMPD performance of these integrated systems and to provide alternative solutions for sustainable city logistics using the potential of crowdshipping and vehicle sharing fleets (VSFs) in the city logistics nodes (CLNs) of CMFMCs. The issues presented by the loading–unloading operations and sustainable crowdshipping scenarios for LMPD in CMFMCs are considered. This paper presents a new performance evaluation model for crowdshipping LMPD in CMFMCs using VSFs. The case study shows that the proposed model enables the analysis of LMPD performance in CMFMCs, taking into account their finite production capacity, and that it facilitates the planning of cargo turnover and the structure of VSFs consisting of e-bicycles, e-cars, and e-light commercial vehicles (e-LCVs). The model is verified based on a case study for sustainable LMPD scenarios using VSFs. The proposed model enables the planning of both short- and long-term logistics operations with the specified performance indicator of VSF usage in CMFMCs. The validity of using the integrated potential of crowdshipping and vehicle sharing services for LMPD under demand uncertainty in CMFMCs is discussed. This study should prove useful for decision-making and planning processes related to LMPD in CMFMCs and large cities.

Optimization of Truck–Cargo Matching for the LTL Logistics Hub Based on Three-Dimensional Pallet Loading

This study investigates the truck–cargo matching problem in less-than-truckload (LTL) logistics hubs, focusing on optimizing the three-dimensional loading of goods onto standardized pallets and assigning these loaded pallets to a fleet of heterogeneous vehicles. A two-stage hybrid heuristic algorithm is proposed to solve this complex logistics challenge. In the first stage, a tree search algorithm based on residual space is developed to determine the optimal layout for the 3D loading of cargo onto pallets. In the second stage, a heuristic online truck–cargo matching algorithm is introduced to allocate loaded pallets to trucks while optimizing the number of trucks used and minimizing transportation costs. The algorithm operates within a rolling time horizon, allowing it to dynamically handle real-time order arrivals and time window constraints. Numerical experiments demonstrate that the proposed method achieves high pallet loading efficiency (close to 90%), near-optimal truck utilization (nearly 95%), and significant cost reductions, making it a practical solution for real-world LTL logistics operations.

Analysis of Factors Affecting Logistic Performance Among Registered Freight and Forwarding Firms in Nairobi County, Kenya

Purpose: The general objective of the study was to establish the environmental factors affecting logistics performance among registered freight forwarding firms in Nairobi County, Kenya. The specific objectives comprised of examining the effect of the internal environment, external environment and firm size on the logistic performance of registered freight forwarding firms in Nairobi County, Kenya. Methodology: This study used a descriptive research design. The study targeted 1676 managing director and senior departmental level managers drawn from the registered freight and forwarding firms. Data was collected using questionnaires. The collected data was entered into SPSS 28 analytical tool where it was coded and analysed. Both descriptive and inferential analysis was applied. Findings: The findings showed that firm size had a positive and significant moderating effect on the relationship between environmental factors and performance of registered freight and forwarding firms in Nairobi County, Kenya. The study concludes that there is a positive and statistically significant relationship between internal environment factors and logistic performance. The study shows that while the structural aspects are important, the cultural and leadership elements play a more pivotal role in enhancing logistic performance. The study further concludes that external environment factors have a positive and significant effect on logistic performance. The study notes that infrastructure, policy and technology are crucial, but the potential benefits of technology may not be fully realized or uniformly adopted across the firms. The study also concludes that firms of all sizes can potentially achieve high logistic performance by focusing on effective resource utilization, strategic market analysis, and continuous development efforts. Unique Contribution to Theory, Policy and Practice: The study recommends that the policymakers should focus on simplifying documentation and customs procedures to reduce delays and improve the overall efficiency of logistic operations. The government should invest and increase support in research and development. The study also recommends that firms should establish clear communication policies that foster teamwork and engagement since encouraging participatory engagement and keeping employees informed of shared goals can spur productivity. Logistical firms should also invest in resources including human resource and financial resources. The firm should recruit and retain adequate and competent personnel to meet organizational goals as well as mobilize financial resources effectively to support investments in technology and infrastructure.

The macroeconomic determinants of trade openness in Latin American countries: A panel data analysis

Background Trade openness shows a positive impact on economic growth, supported by economic theory, and export diversification and economic complexity show a positive dynamic in trade openness in the world; however, a specificity is generated in South American countries. Therefore, the objective of the research is to analyse the macroeconomic determinants of trade openness in Latin American countries. Methods The research approach was quantitative and explanatory using panel data methodology from the databases of the World Bank, Harvard University and the Economic Commission for Latin America and the Caribbean for the period 2000-2020. Results The fixed effects panel data model showed that the variables that had a negative impact on trade openness were GDP, the economic complexity index and the logistic performance index, while the variables that had a positive impact were exports of high-tech products (a proxy for innovation), exports, imports, research and development expenditure and interregional trade in goods. Conclusions Therefore, during the analysis period of 2000-2020 in South America, based on the panel data analysis under fixed effects, a total of 8 countries had a negative impact on trade openness, and only the economies of Chile, French Guiana, and Brazil had a positive impact on trade openness; these economies are characterized by their better performance in the economic complexity index, their higher percentage of budget for research and development expenses, and their trade policies oriented towards the industrialization of their value-added products.

Avoidance of Medicine Wastage in Private Clinics In Hong Kong: Practitioners’ Perspectives

Hong Kong with its well-established healthcare and medicine system and professional health services is one of the renowned healthiest places in the world. In fact, Hong Kong's healthcare system is running on a dual-track basis comprising public and private sectors. This study intends to explore medicine waste management and sustainability. First, we examine the existing phenomenon of Hong Kong medicine waste. Also, we discuss the causes of medical waste from a private clinic doctors' perspective. In addition, we identifies possible policies and recommendations to minimize the medicine wastage in private clinic in Hong Kong as well as improve the healthcare supply chain practices. Qualitative research with in-depth interviews of doctors and medical practitioners have been carried out to gather their views and opinion of medication wastage, including the current medicine waste situation and the means of handling the expired medicines. Also, the study analyzes the centralized procurement platform effectiveness and suggests some possible policies for government to adopt. Interviewees mentioned that medication waste has occurred over decades. Medicine wastages are not only financial burdens, but also social burdens. If the medication waste problem cannot be alleviated, it will affect the population health and environment in the long run. An all-rounded healthcare supply chain with efficient logistics operations would help the government to collect excess medicines from private clinics and redistribute to some NGOs. In fact, all parties including manufacturers, distributors, prescribers, and patients have the responsibilities to maintain and implement suitable policies to prevent bulk medicine waste. This research study provides the foundation of medicine wastage in private clinics in Hong Kong. Future research can investigate the medicine wastage in other aspects as well as consolidate the literatures in both industrial and public perspectives.

Process Mining in der Intralogistik

Abstract The application of process mining opens up a wide range of possibilities for logistics, such as the identification of bottlenecks, the optimization of throughput times and the more efficient use of resources. However, in an area as dynamic and vulnerable as logistics, there are specific challenges that make the application of process mining difficult and therefore require special attention. A structured approach is therefore required to successfully implement process mining in practice. This publication presents a methodology that supports companies in effectively integrating process mining into their internal logistics operations. It includes project initialization, the extraction and preparation of the data to be analyzed, the execution of analyses, the interpretation of the results and the derivation of measures.

FORMATION OF A SYSTEM FOR ASSESSING THE EFFECTIVENESS OF INNOVATIVE DEVELOPMENT OF LOGISTICS ACTIVITIES OF MOTOR TRANSPORT ENTERPRISES ENGAGED IN FREIGHT TRANSPORTATION IN TERMS OF SUSTAINABLE DEVELOPMENT

The article discusses the importance of implementing innovations at road transport enterprises in the context of achieving the region's sustainable development goals. The author emphasizes that road transport enterprises are significant sources of harmful emissions and environmental pollution, so using innovative technologies, such as electric vehicles, hybrid cars, and alternative fuels, is an important tool for reducing the negative environmental impact. In particular, these technologies help to reduce greenhouse gas emissions and other harmful substances, which is in line with Sustainable Development Goals 7 (access to modern energy), 13 (combating climate change), and 15 (protecting terrestrial ecosystems). In addition, innovations in transport technologies, such as automated driving systems, help to improve road safety and reduce the number of road accidents, which is in line with Goal 3 (good health and well-being). The creation of new jobs and infrastructure development through the construction of electric charging stations and the introduction of intelligent transport systems (smart cities) are also linked to Sustainable Development Goals 9 (sustainable infrastructure) and 11 (sustainable urban development). The author analyses the performance indicators of innovations at motor transport enterprises, taking into account economic, social, and environmental aspects. Particular emphasis is placed on the adaptation of these indicators to the current realities of Ukraine. Using game theory, the article develops a model for the selection of optimal strategies for motor transport enterprises and the region. This model allows us to find the Nash equilibrium - a situation where both parties achieve the optimal result. Enterprises that implement innovations not only improve their own performance indicators, but also contribute to the achievement of sustainable development goals of the region. The article also presents two sets of strategies: for the development of logistics activities of a motor transport enterprise and the sustainable development of the region. Both approaches aim to comprehensively improve the region's environmental, economic, and social situation. The conclusions emphasize the importance of implementing innovation development assessment systems as a tool for making strategic decisions and improving the efficiency of logistics operations.

Factors Affecting Logistics Performance on Malaysian Retail Industry: A Conceptual Paper

Factors Affecting Logistics Performance on Malaysian Retail Industry: A Conceptual Paper

Exploring the circular last mile: reusable packaging in home delivery of food and groceries using a design science approach

ABSTRACT The market for home deliveries of food and groceries has been growing in the last years, and with it so have the associated environmental impacts: emissions from the delivery routes, energy for the cold chain and packaging waste are some of the main concerns. The purpose of this paper is to contribute with knowledge to support the development and implementation of circular retail supply chains, with focus on customer involvement and logistics operations in home deliveries of food and groceries. This study is based on a design science approach that follows three main steps: (1) development of the ‘circular delivery concept’ (i.e., the artefact), (2) field-test in real-life conditions and (3) key-learnings and implications on theoretical, managerial, and policy domains. The feedback from the actors involved in the concept (customers, production/warehouse staff, delivery drivers and e-tailer management) was collected through semi-structured interviews, observations, and workshops. Results show potential of the circular delivery concept at test, with customers and delivery drivers recognising positive aspects and a good potential from the new setting. The warehouse staff and the management board, were, however, sceptical of the concept and expressed concerns on the practicability to scale it up because of the challenges in operationalising it in the warehouse. The main barriers found in this study relate to the need to implement new processes for circular supply chains in efficient and cost-effective ways, and to get customers more actively involved and to assume their responsibilities. For the latter, the added value needs to be conveyed more clearly and pragmatically so that the customer recognises its value as obvious and clear. Managerial and policy implications were deduced, as well as theoretical implications that contribute to the theory of consumption value.

Logistics and port performance of South Africa: Do the numbers add up?

N/A

Dynamic collaborative truck-drone delivery with en-route synchronization and random requests

Coordinated truck and drone delivery is gaining popularity in logistics as it can greatly reduce operation costs. However, existing studies on related operations management problems typically ignore the following important features: (i) the random appearance of requests, which require operators to dynamically respond to the requests; and (ii) the decisions of optimal launch and retrieval locations for trucks and drones instead of fixed to customer locations, which can significantly impact the overall time costs. To tackle these challenges, this study investigates the dynamic collaborative truck-drone routing problem with randomly arriving requests and synchronization on routes. We model the problem as a Markov Decision Process (MDP) and solve the MDP via a reinforcement learning (RL) approach. The proposed RL approach determines: (i) whether each request should be serviced upon arrival, (ii) which truck or drone should be assigned for the request, and (iii) the optimal en-route take-off and landing positions for paired trucks and drones. We further employ a framework of decentralized learning and centralized dispatching in RL to increase performance. Numerical experiments are conducted to assess the proposed solution approach on instances generated based on both the Solomon dataset and real-world operational data of a logistics operator in Singapore over several benchmark algorithms under various battery endurance levels of drones and distinct transportation scenarios including node-based dynamic collaborative truck-drone routing problem, dynamic non-collaborative truck and drone routing problem, and dynamic vehicle routing problem. The results show that our RL solution outperforms the benchmark algorithm in total profit by an average of 28.03 %, and our en-route takeoff and landing scenario outperforms the benchmark scenarios in total profit by an average of 8.43 % in multi-day instances. Additionally, compared to the traditional node-based landing scenario, employing our en-route takeoff and landing strategy can save 0.9 h/(drone*day) of waiting time on average.

Modeling inter-organizational business process governance in the age of collaborative networks

Collaborative networks require inter-organizational business process governance (IO-BPG) mechanisms to define ownership over shared resources and activities, accountability over operations, inter-organizational roles and responsibilities, and strategic partner alignment. We developed an IO-BPG modeling approach aiming to incorporate (1) IT governance activities (e.g., IT performance measurement), (2) data governance activities (e.g., data strategy management), and (3) “shadow” parallel governance-related operations. Resulting from a design science research project, our contributions include the building blocks (domain attributes, ontology, and requirements) of a novel BPMN extension, its demonstration in logistics operations, its evaluation, and design principles to guide IO-BPG modeling. Suggestions for the development and evaluation of future BPMN extensions are also highlighted based on the lessons learned in this project. For practitioners, our contribution can improve accountability reports over data assets and operations, identify dataset ownership, assist in the coordination of governance activities in networked businesses, and comply with regulations and strategic partnership agreements.

Разработка подхода к интегрированному планированию в цепочках поставок приборостроительной отрасли

Purpose: the article proposes an approach to integrated planning in supply chains of the instrument-making industry, aimed at improving the efficiency of coordination between their main participants. Methods: the study used methods of system analysis, statistical analysis and expert assessments, which made it possible to evaluate current approaches to planning and propose an approach to integrated planning based on modern digital technologies used in the performance of the planning function. To obtain the results of the study, official statistical data on the productivity and economic indicators of the instrument-making industry, data on logistics operations and supply chains of various enterprises in the industry were used. Results: the main scientific result is the approach to the development of integrated planning in supply chains developed by the author. The study also provided practical recommendations on the use of management methods at different stages of the formation of an integrated planning system. Practical significance: the practical significance of the study lies in the possibility of applying the proposed recommendations at enterprises of the instrument-making industry to improve the efficiency of supply chain management. The implementation of the developed methods will allow enterprises to adapt to dynamic market conditions, reduce costs and improve coordination of the actions of private logistics chain participants. The results of the study can be used to develop and improve planning systems in organizations in the instrument-making industry.

Stage-Specific Multi-Objective Five-Element Cycle Optimization Algorithm in Green Vehicle-Routing Problem with Symmetric Distance Matrix: Balancing Carbon Emissions and Customer Satisfaction

This study presents a bi-objective optimization model for the Green Vehicle-Routing Problem in cold chain logistics, with a focus on symmetric distance matrices, aiming to minimize total costs, including carbon emissions, while maximizing customer satisfaction. To address this complex challenge, we developed a Stage-Specific Multi-Objective Five-Element Cycle Optimization algorithm (MOFECO-SS), which dynamically adjusts optimization strategies across different stages of the process, thereby enhancing overall efficiency. Extensive comparative analyses with existing algorithms demonstrate that MOFECO-SS consistently outperforms in solving the multi-objective optimization model, particularly in reducing total costs and carbon emissions while maintaining high levels of customer satisfaction. The symmetric nature of the distance matrix further aids in achieving balanced and optimized route planning. The results highlight that MOFECO-SS offers decision-makers flexible route planning options that balance cost efficiency with environmental sustainability, ultimately improving the effectiveness of cold chain logistics operations.

Analysing cross-border logistics operations for performance improvement: development and validation of a reference model

AbstractThe critical role played by cross-border logistics (CBL) systems in sustaining fast, efficient and responsive global supply chains is widely recognised. However, scholarly research focusing on CBL systems is limited, which means that theoretical frameworks and methodological approaches available for analysing and improving CBL operations are underdeveloped. As such, coordination among diverse stakeholders, meeting regulatory requirements, adapting to a rapidly evolving technological environment, and limited capacity for investing in high-value assets, all remain ongoing challenges hindering the smooth and swift flow of cargo across borders. With a view to addressing these challenges and research gaps, this paper develops a reference model for analysing and improving CBL-specific processes. Seven underlying process dimensions have been identified following a rigorous methodological approach for the modelling, analysis and improvement of CBL operations. The efficacy of the reference model is demonstrated using two purposive case applications. The reference model also helps identify potential technological interventions to improve operations and benchmark CBL systems, operations and processes.

A novel method for evaluating ship concept performance in transport systems

Abstract Transport carries significant external costs such as climate change, accidents, pollution, and road congestion, driving national and international strategies for the development of new transport concepts. This includes shifting larger cargo volumes away from roads to more sustainable transport modes such as waterborne. The SEAMLESS project was launched in 2023 to answer to these needs by developing technology for autonomous waterborne zero-emission feeder-loop services. The realisation of such services depends on their modal competitiveness. Autonomous ships are expected to reduce transport costs and emissions, and ultimately improve logistical performance. There are, however, few published studies that quantify these impacts of autonomy. Furthermore, commercial waterborne autonomous transport services do not exist yet, limiting the possibilities for empirical analysis. Hence, research is needed to address exactly how and to what extent, autonomy improves competitiveness in different applications. This paper addresses the need for more empirical analyses of innovative waterborne transport performance, by presenting a novel method for evaluating ship concept performance in transport systems. The impacts of design choices are captured through hydrodynamic and logistical simulations. The method can be applied to transport systems consisting of both conventional and novel ship designs, operating on one or more routes including transhipments. It is implemented in the software SIMPACT and applied to a case study which establishes a shortsea feeder-loop service in the Bergen area in Norway. The Bergen municipality has decided that the container terminal is to be moved out of the city centre to reduce local traffic and emissions. However, in the absence of a competitive waterborne transport service in this region, the relocation will have the unfortunate consequence of an estimated annual net increase in regional truck traffic of 40,000 additional truck trips over 25km. By means of the proposed methodology, this paper investigates the feeder-loop concept and compare its quantified performance to truck transport and finds that competition is feasible.

Logistics Performance Index-driven in operational planning for logistics companies: A smart transportation approach

The responsibility of Logistics Companies (LCs) extends beyond simply handling logistical processes and choosing transportation routes; they focus on being competitive and efficient in their operations. In multiple origins and destinations networks, LCs attempt to select the most optimal routes from each point. To address this challenge and reduce the time needed to identify potential routes, a novel method has been developed in this research for LCs. In operational planning, additional factors need to be considered to increase efficiency, customer satisfaction, and competitiveness. To confront this issue, the study proposes a novel model and contributions, inspired by the LPI, to apply the transformative impact of smart ports, the integration of smart containers, the choices of clearing and forwarding agents and port operators, and time uncertainty in the multi-objective framework. Specifically, the mathematical model's objectives include cost, time, customer satisfaction, and environmental impact in the periodic multimodal network. An innovative customer satisfaction function is introduced by integrating the selection of smart containers and smart ports, emphasizing their impact on enhancing customer satisfaction, while addressing time uncertainty through a chance-constrained approach and coefficients of variation. The model is solved using goal programming, and the results show that smart ports and smart containers can majorly affect transportation time and customer satisfaction. Furthermore, comparing the results to other studies demonstrates its superiority in decision-making for LCs, particularly by including time uncertainty and the role of clearing and forwarding agents and port operators. Therefore, the model holds practical significance in lowering costs, enhancing customer satisfaction, and facilitating smart international logistics. This research offers insights that are not only useful for the LCs but also for other stakeholders in the transport industry.

Influence of Logistics Performance on Economic Growth in BRICS Countries

Influence of Logistics Performance on Economic Growth in BRICS Countries