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The inventory levels of pickup points play an important role for the same-day or next-day pickup and delivery services. The previous inventory optimisation research usually makes an assumption about demand distribution, does not use the real dataset or consider shipping strategies for this problem. In this study, we introduce a new strategy, mixture of anticipatory and emergency shipping, and propose forecasting-optimisation integrated approach to optimise multi-items' inventories in each pickup point based on big data analysis. We explore a real dataset including 23,808,261 records with 54 pickup points and 4018 items. We first cluster the dataset based on the distances between pickup points and the warehouse, then, implement the forecasting-optimisation integrated algorithms to select the more profitable strategy for each group. The result indicates that compared with the original algorithms, our proposed approach can effectively increase the profits, particularly, the novel algorithm, Long Short-Term Memory networks – Quantile Regression, performs better. Additionally, we find that the 100% anticipatory shipping is not necessarily superior to emergency shipment, when the pickup point is farther from the warehouse, the advantage of emergency shipment is more significant. However, the mixture of anticipatory and emergency shipping can contribute to higher profits for online retailers. [ABSTRACT FROM AUTHOR]

This paper investigates a single-vendor, multiple-buyer coordinated supply chain under stochastic demand. Each buyer implements a continuous review policy, and the shortage quantity is fully back-ordered. The lead time for the first shipment includes setup, production, and transportation times, while the lead time for the remaining shipments includes only transportation time. The production time is a function of production lot and production rate, which are both decision variables, and the setup and transportation times are controllable as well. For each buyer, the safety stock in the first replenishment cycle is not necessarily identical to that in the remaining cycles. Two successive shipments from the vendor to a buyer may have different sizes, and their ratio is a decision variable. The problem is finding the production and inventory replenishment policy, production rate, and lead times that minimise the long-run expected total cost per time unit. We demonstrate properties satisfied by the cost function and develop an optimisation algorithm, whose performance is compared to a benchmark algorithm based on a commercial solver in a numerical experiment. The experiments also investigate the benefits stemming from the proposed model when compared to models reproducing situations that leverage some or any of the controlled factors. [ABSTRACT FROM AUTHOR]

Clay sealings (cretulae) have traditionally been assumed to have been used in ancient administrative systems to secure the shipment of commodities and to account for their receipt. However, research in Western Asia has revealed that they were primarily used as a complex administrative tool in the management of storehouses and the goods they contained, ensuring the personal accountability of the individuals under whose seal or combination of seals particular items were stored. Although stamp seals are relatively common finds in the Indus Civilization, clay sealings are not as numerous as in contemporaneous sites throughout Western Asia. This rarity has led to speculation about the actual use of seals in the Indus Civilization. However, the study of an exceptional assemblage of clay sealings found at the Indus site of Lothal in Gujarat, India, has shed light on the function and use of these objects in the Indus Civilization. In particular, the stratigraphic analysis of the discovery context has made it possible to consider the existence of an administrative archive comparable to those excavated in Western Asia. [ABSTRACT FROM AUTHOR]

The growth of e‐commerce trade has led to more parcel shipments, causing an increase in corrugated board box packaging. Individually shipped boxes often sustain more damage, like crushing or puncturing, compared to pallet‐transported boxes. In contrast to the known relationships between containerboard properties and box compressive strength, there is no standard method for designing corrugated board against puncturing, which can result in damages, customer dissatisfaction and costly returns. A hole is typically seen as a severe compromise to package integrity, whereas some crushed boxes can be acceptable for nonfragile items. Addressing this, this research has focused on developing design equations linking containerboard and corrugated board properties to resistance against puncturing. These equations give the energy loss of an impacting object that would cause a hole and define the energy absorbance limit of the material. The equations enable material design aimed at minimizing puncturing risks based on specific distribution chain conditions, like fall heights and velocities. [ABSTRACT FROM AUTHOR]

In safety‐critical systems engineering, regulations such as Automotive SPICE, ISO26262, or ED‐109A mandate software quality assurance measures to provide evidence that the developed system is high quality. The constraints that define quality assurance conditions during the engineering life cycle are often non‐trivial. This paper addresses the challenges, engineers face who are unfamiliar with the precise constraints of various projects (e.g., when newly joining a company or switching between departments). Understanding how to fulfill a constraint is a time‐consuming and challenging task as an engineer needs to determine the most suitable option (out of potentially many) to fulfill a constraint violation. To this end, we propose a guidance action ranking framework to provide engineers with the most relevant guidance actions. Our primary ranking algorithm analyzes in the background the actions that engineers have made in the past to resolve a constraint violation without requiring explicit feedback from them. We evaluated our framework on two real‐world data sets: an open‐source drone management and an industrial air traffic control software system. Concretely, we replay past engineering activities and measured whether, in the case of a constraint violation, our suggested guidance actions were indeed selected by the engineer. The evaluation results revealed that learning from prior guidance actions effectively identifies the most appropriate guidance actions (ranked top 1 or 2) when compared to ranking algorithms based on action simplicity and artifact property change frequency. Specifically, we achieve a median MRR of 0.95 for the first case study and 0.94 for the second case study: an improvement of 80% and 100% over the baseline. Additionally, we observed that the simplicity of a guidance action does not reliably indicate its suitability for fulfilling a constraint, whereas learning from prior change operation property out‐performed simplicity‐based ranking but did not surpass guidance frequency‐based ranking. [ABSTRACT FROM AUTHOR]

Background: The concept of Hyperconnected Megacity Parcel Logistics (HMPL) was introduced in 2018 and aims to enhance the efficiency, responsiveness, resilience, and sustainability of parcel movements in megacities. However, evaluating such fundamental solutions presents challenges and requires a comprehensive understanding of all stakeholders and decisions involved. Methods: This study introduces a discrete-event agent-based simulation platform that encompasses critical stakeholders and addresses various levels of decision-making. This platform provides an opportunity to evaluate key decisions within an HMPL structure. Results: To demonstrate the capability of the simulator, we assess the impact of package routing and consolidation strategies facilitated by HMPL compared to traditional practices. Preliminary findings suggest that increased interconnection among nodes in HMPL reduces transit times, thereby enabling tighter customer delivery services. However, examining different consolidation heuristics reveals potential trade-offs between handling and shipping costs under fixed shipment schedules, prompting further investigation into dynamic shipment services. Conclusions: The findings of this study suggest that the benefits of innovative approaches in a complex environment, such as parcel logistics, cannot be evaluated in isolation from other decisions. Accurate assessment of the ultimate outcomes and underlying trade-offs requires multi-faceted models that incorporate all key variables. [ABSTRACT FROM AUTHOR]

To investigate the effect of uncertain demand on various omnichannel distribution network strategies and analyze the impacts of various online order fulfillment policies, a two‐staged network optimization model is built. The two stages are a deterministic model to define the optimal distribution network and a simulation model to determine the optimal network flow to maximize the total profit for a given distribution network and online order fulfillment policy. This study shows the importance of taking demand uncertainty, requested delivery time, and customer service level (CSL) into account in designing an omnichannel distribution network. The results of the simulation model indicate that shipments from warehouse (SFW) and hybrid strategies more successfully cope with variation because there is a greater profit decline in shipments from store (SFS) strategies. The results also show that applying a dynamic assignment policy plays an important role in handling variation in demand. The study shows that, as demand uncertainty and CSL increase, having products available in central repositories becomes even more important to cope with demand variation. The study also indicates SFS strategies that seem more profitable in the assumed‐to‐be deterministic model might be misleading because SFS strategies become less profitable (compared to SFW strategies) when demand uncertainty is taken into account. [ABSTRACT FROM AUTHOR]

This study introduces an innovative smart impact detection system designed for real-time monitoring of shipment status and path integrity. Leveraging the advanced capabilities of the ESPRESSIF ESP32-S3-MINI-1U-N8 microcontroller, which integrates Wi-Fi, a display, a memory card slot, and accelerometers, this detector represents a significant advancement in shipment tracking technology. The device is engineered to continuously measure impact magnitudes in terms of g-force, and records data when predefined impact thresholds are exceeded. These data are then wirelessly transmitted to a remote server, providing users with the ability to track shipment status and path via a dedicated application. The performance testing revealed impact measurements ranging from −0.5 to 2 g, with occasional peaks reaching approximately 4.5 g, demonstrating the system's sensitivity and reliability in diverse conditions. This smart impact detector not only facilitates continuous monitoring, but also enhances the ability to respond swiftly to potential shipment violations, thus providing a novel solution for ensuring shipment integrity. This research contributes to the field by presenting a comprehensive real-time impact detection system that integrates modern microcontroller technology with effective monitoring capabilities, setting a new benchmark for shipment tracking systems. [ABSTRACT FROM AUTHOR]

The present paper seeks to conceptualise the notion of complementarity with the help of rail-based commodity flow data in one of the most prominent railway towns in India i.e. PanditDeenDayalUpadhyaya Nagar (Mughal Sarai). Referring to the theoretical notion of 'complementarity' and a modified form of 'gravity model' from the 'Family of Spatial Interaction Models', this research puts an intensive discussion forward on the existing nature of spatial interaction of PanditDeenDayalUpadhyaya Nagar (Mughal Sarai) with its complementary areas and a comparison of these areas in terms of their relative complementarity with the town concerned. The resultant outcome in the form of a Complementarity Index, portrays a different, if not entirely contradictory picture from the crude values of material shipments to PanditDeenDayalUpadhyaya Nagar (Mughal Sarai). This analysis thus well-indicates that merely supplying greater amount of commodities of any kind does not necessarily reflect greater complementarity and vice versa. Therefore, a more comprehensive analysis of commodity flows is imperative to have a deeper insight into the notion of spatial interaction. [ABSTRACT FROM AUTHOR]

Before leaving the factory, lithium-ion battery (LIB) cells are screened to exclude voltage-abnormal cells, which can increase the fault rate, troubleshooting difficulty, and degrade pack performance. However, the time interval to obtain the detection results through the existing voltage-abnormal cell method is too long, which can seriously affect production efficiency and delay shipment, especially in the mass production of LIBs when facing a large number of time-critical orders. In this paper, we propose a data-driven voltage-abnormal cell detection method, using a fast model with simple architecture, which can detect voltage-abnormal cells based on the multi-source time series data of the LIB without a time interval. Firstly, our method transforms the different source data of a cell into a multi-source time series data representation and utilizes a recurrent-based data embedding to model the relation within it. Then, a simplified MobileNet is used to extract hidden feature from the embedded data. Finally, we detect the voltage-abnormal cells according to the hidden feature with a cell classification head. The experiment results show that the accuracy and average running time of our model on the voltage-abnormal cell detection task is 95.42% and 0.0509 ms per sample, which is a considerable improvement over existing methods. [ABSTRACT FROM AUTHOR]

An investigation is conducted in this paper into a performance analysis of fully intuitionistic fuzzy multi-objective multi-item solid fractional transport model (FIF-MMSFTM). It is to be anticipated that the parameters of the conveyance model will be imprecise by virtue of numerous uncontrollable factors. The model under consideration incorporates intuitionistic fuzzy (IF) quantities of shipments, costs and profit coefficients, supplies, demands, and transport. The FIF-MMSFTM that has been devised is transformed into a linear form through a series of operations. The accuracy function and ordering relations of IF sets are then used to reduce the linearized model to a concise multi-objective multi-item solid transportation model (MMSTM). Furthermore, an examination is conducted on several theorems that illustrate the correlation between the FIF-MMSFTM and its corresponding crisp model, which is founded upon linear, hyperbolic, and parabolic membership functions. A numerical example was furnished to showcase the efficacy and feasibility of the suggested methodology. The numerical data acquired indicates that the linear, hyperbolic, and parabolic models require fewer computational resources to achieve the optimal solution. The parabolic model has the greatest number of iterations, in contrast to the hyperbolic model which has the fewest. Additionally, the elapsed run time for the three models is a negligible amount of time: 0.2, 0.15, and 1.37 s, respectively. In conclusion, suggestions for future research are provided. [ABSTRACT FROM AUTHOR]

Copyright of Magazine of Historical Studies & Archaeology is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Compound wind and precipitation extremes (CWPEs) can severely impact natural and socioeconomic systems. However, our understanding of CWPE future changes, drivers, and uncertainties under a warmer climate is limited. Here, by analyzing the event both on oceans and landmasses via state‐of‐the‐art climate model simulations, we reveal a poleward shift of CWPE occurrences by the late 21st century, with notable increases at latitudes exceeding 50° in both hemispheres and decreases in the subtropics around 25°. CWPE intensification occurs across approximately 90% of global landmasses, and is most pronounced under a high‐emission scenario. Most changes in CWPE frequency and intensity (about 70% and 80%, respectively) stem from changes in precipitation extremes. We further identify large uncertainties in CWPE changes, which can be understood at the regional level by considering climate model differences in trends of CWPE drivers. These results provide insights into understanding CWPE changes under a warmer climate, aiding robust regional adaptation strategy development. Plain Language Summary: Concurrent wind and precipitation extremes (CWPEs), a typical case of compound weather events, can cause flooding and strong winds that can paralyze public transportation, trigger power outages, and destroy houses and shelters. Furthermore, CWPE over the ocean can endanger the shipment of goods and its logistics. Yet, our understanding of the projected changes, underlying drivers, and uncertainties under a warmer climate is limited. Here, analyzing for the first time CWPEs both on global oceans and landmasses allows us to reveal a poleward shift of CWPEs at the global scale in response to climate change. We show that changes in precipitation extremes play a dominant role in determining the future changes in the frequency and intensity of CWPEs. Furthermore, at the regional level, we reveal substantial uncertainties in projections due to differences between the used climate models. We illustrate that these uncertainties are due to model differences in trends of CWPE drivers and argue that they should be addressed explicitly in impact assessments for guiding the development of robust adaptation strategies. Key Points: An intensification and poleward shift of compound wind and precipitation extremes (CWPEs) will occur in a warmer climateMost changes in frequency and intensity of CWPEs stem from changes in precipitation extremesSubstantial uncertainties at the regional level in projections of CWPEs are due to structural model differences [ABSTRACT FROM AUTHOR]

Warehouses recently face increasing stress imposed by a volatile customer demand and increasing customer expectations in terms of ever shorter order response times. In that respect, warehouses more and more offer same-day and next-day shipment conditions. However, same-day shipment promises are challenging to fulfil, especially as the order fulfilment process operates against fixed deadlines imposed by the predefined truck departure times. As a natural mitigation strategy, warehouses set a cutoff point and offer same-day shipment only to customers that order until the cutoff point, but next-day shipment to all customers ordering thereafter. Setting an appropriate cutoff point is challenging as it affects multiple facets of the service quality, such as the order response time and the service level. In this paper, we study the design of cutoff-based shipment promises for stochastic deadline-oriented order fulfilment processes in warehouses. We present a discrete-time Markov chain model for exact steady-state performance analysis and propose two novel performance measures – α - and β - cutoff service level – for service level measurement in these systems. We numerically show the benefit of cutoff-based shipment promises. Even with a late cutoff point, there is a significant gain in the system performance. Furthermore, we find that warehouses should set the cutoff point such that it balances customer expectations in terms of service level and order response time. Finally, warehouses can improve their shipment promises when referring to β - instead of α - cutoff service level and by implementing measures reducing the utilisation and the variabilities of the order fulfilment process. [ABSTRACT FROM AUTHOR]

The main motivation for this work is the design of context-sensitive systems, involving a human-agent team. More precisely, the participants in the current context, are human beings and software agents, who have to coordinate themselves for the collaborative achievement of a complex task. We propose a model of interaction between these heterogeneous entities (humans, software agents) based on decision matrices inspired from game theory. The case study concerns the traffic management through intersections, involving several groups composed of human operators and software agents (playing the role of assistants), in a participatory simulation. An evaluation of the results obtained is presented in order to show the feasibility of the proposed approach. We show that despite its simplicity, the interaction model is relatively efficient, because it takes into account context characteristics and the potential availability of software agents. [ABSTRACT FROM AUTHOR]

Due to the limited internal space of urban tunnels and the inability to manoeuvre the vehicles in them, critical situations will be created for vehicle traffic in accidents. Under these situations, traffic management strategies should be utilized for improving traffic status. The common and applicable strategies in these situations include traffic flow direction, line management, and ramp control. Accordingly, this research is conducted to determine the impact of each of these strategies in the occurrence of the most critical accident in the Niayesh and Resalat tunnels of London. Therefore, the studied areas of tunnels are initially simulated by software and traffic data at the peak hours of the morning in 2013, and then the amounts of traffic flow parameters, the total travel time, delay time, stop time, flow density, and the average velocity of each strategy are studied by defining four different scenarios. The results of conducted survey and analyses indicate that adopting the target strategies of this paper improves the conditions of traffic functional parameters; and according to the comparisons, the traffic flow direction strategy has the highest efficiency in Niayesh tunnel and the ramp control strategy has the highest efficiency in Resalat tunnel. [ABSTRACT FROM AUTHOR]

Integrating vendors' and buyers' production-inventory systems can significantly reduce the total costs incurred by both parties. In this paper, we study the synchronised multi-vendor multiple-buyer integrated production-inventory system with a production flow where the lot sizes follow a geometric sequence. We model this new problem with the objective to minimise the total cost incurred by the vendors and the buyers and determine the optimal production shipment policy. The computational experiments realised on real case study show the efficiency of the developed model for optimising production shipment and synchronisation of vendor-buyer inventories. [ABSTRACT FROM AUTHOR]

This research aims to solve an integrated production, storage and distribution planning problem in a multi-level multi-product logistics system. The work was conducted in collaboration with a leading mining industry. The present research presents a mixed-integer linear program inspired by the classical Multi-Level Lot-Sizing model to solve the problem. It combines several aspects related to (1) multi-level and multi-product production units, (2) multi-level and multi-product storage units and (3) train transportation with time windows. Besides the standard features of lot-sizing problems, this work encompasses further aspects related to mining activity precisely and, more generally, to the structural specifications of continuous production processes. The objective is to hierarchically satisfy deterministic demand, minimise the total number of switch-offs of production units, and minimise total operational costs. On a sizeable real data-set obtained from our industrial partner, we demonstrate the benefit of integrating decisions in terms of improving demand satisfaction rates, increasing resource efficiency, and minimising total operational costs. In addition, we study the cost structure and provide a detailed cost sensitivity analysis. Finally, this work evaluates the upstream and downstream propagation of decisions in the logistics system and underlines the benefits in terms of flexibility offered by the global approach. [ABSTRACT FROM AUTHOR]

Copyright of Umsatzsteuer-Rundschau is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper aims to coordinate a shipment lead time hedging (SLTH) problem between a building contractor and a logistics provider in the prefabricated construction supply chain (PCSC). In the PCSC, untimely (early or late) delivery of prefabs can lead to project time and cost overruns. To mitigate this challenge, the building contractor requires the logistics provider to reduce the shipping time variability, which is termed the SLTH strategy. While this benefits the building contractor, it also puts more investment and operational pressures on the logistics provider. To solve this conflict, we introduce a coordination mechanism which involves two terms: an SLTH level related cost term is charged by the logistics provider to the building contractor, and a constant transfer term is adopted to fairly allocate the system surplus. Three decentralized models are investigated: i.e., two Stackelberg game models with alternative decision-making sequences and an equal power model. Further comparative analysis and numerical studies reveal that our proposed coordination mechanism increases the SLTH level and ensures a win–win situation. Moreover, some interesting managerial implications are derived. [ABSTRACT FROM AUTHOR]

The issue of the transport of goods is well-known, yet, in practice, there are often cases of damaged shipments due to improper storage and inappropriately chosen transport technology. Many cases are due to ignorance of the basic characteristics of the cargo and, consequently, its transport characteristics. Vehicle dynamics is crucial to the design of proper cargo securing; therefore, this article provides the values of longitudinal and lateral acceleration of a 16.5 m semi-trailer vehicle combination for test routes of length of 10,827 km on highways and other roads in Slovakia, Austria, and Germany from the monitoring of goods. The horizontal acceleration of 0.2 g is considered as the minimum stability of the load unit that should withstand transport. A load unit with a stability from 0.2 g to 0.3 g could be considered as the weakest load unit. The test results show that even the weakest load units such as these can be damaged in transports, as semi-trailer vehicle combinations still reach longitudinal ax1000 and lateral ay1000 accelerations between 0.2 g and 0.3 g relatively frequently. Acceleration events higher than 0.3 g occur very rarely, at 1.4 event/1000 km for roads, but only 0.1 event/1000 km for highways from our test transports. We have demonstrated through our research that it is necessary for the load units to have a minimum stability of 0.2 g. We can conclude that load units with a stability of less than 0.2 g are completely unacceptable for transport without additional securing because we obtained 70.3 acceleration events per 1000 km in the interval from 0.1 g to 0.2 g on highways but 1148.1 events per 1000 km on other roads. There is a big difference between the number of acceleration events per 1000 km on roads and highways for all acceleration intervals, which means that there is a substantially lower probability of damaging the weak load units on highways than on other roads. [ABSTRACT FROM AUTHOR]

We study a shipment consolidation problem commonly faced by companies that outsource logistics operations and operate in a commit-to-delivery mode. It involves delivering a given set of orders to their destinations by their committed due times using multiple shipping methods at the minimum total shipping and inventory cost. The shipping cost is generally nonlinear in shipping quantity and can be represented by a subadditive piecewise linear function. We investigate two shipping scenarios, one involving long-haul shipping only and the other involving joint long-haul and short-haul shipping. We develop analytical results and solution algorithms for the shipment consolidation problem under each shipping scenario. The problem under the first shipping scenario is shown to be strongly NP -hard. We find that a simple policy, called the First-Due-First-Delivered (FDFD) policy, which assigns orders with earlier delivery due times to shipping methods with earlier destination arrival times, is very effective. This policy enables us to develop a polynomial time algorithm, which not only solves the problem under the concave shipping cost structure optimally but also achieves a performance guarantee of 2 for the problem under the general subadditive shipping cost structure. For the problem under the second shipping scenario, we extend the FDFD policy for long-haul shipping and derive another policy, called the No-Wait policy, for short-haul shipping. We use these policies to develop a polynomial time algorithm and analyze its performance guarantee. Our computational experiments show that the algorithm significantly outperforms a commercial optimization solver, and its performance is robust across different parameter settings that reflect various practical situations. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data and e-companion are available at https://doi.org/10.1287/mnsc.2023.4835. [ABSTRACT FROM AUTHOR]

Despite more than 40 years of counterdrug interdiction efforts in the Western Hemisphere, cocaine trafficking, or "narco-trafficking", networks continue to evolve and increase their global reach. Counterdrug interdiction continues to fall short of performance targets, due to the adaptability of narco-trafficking networks and spatially complex constraints on interdiction operations (e.g., resources, jurisdictional). Due to these dynamics, current modeling approaches offer limited strategic insights into time-varying, spatially optimal allocation of counterdrug interdiction assets. This study presents coupled agent-based and spatial optimization models to investigate the co-evolution of counterdrug interdiction deployment and narco-trafficking networks' adaptive responses. Increased spatially optimized interdiction assets were found to increase seizure volumes. However, the value per seized shipment concurrently decreased and the number of active nodes increased or was unchanged. Narco-trafficking networks adaptively responded to increased interdiction pressure by spatially diversifying routes and dispersing shipment volumes. Thus, increased interdiction pressure had the unintended effect of expanding the spatial footprint of narco-trafficking networks. This coupled modeling approach enabled the study of narco-trafficking network evolution while being subjected to varying interdiction pressure as a spatially complex adaptive system. Capturing such co-evolution dynamics is essential for simulating traffickers' realistic adaptive responses to a wide range of interdiction scenarios. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of Chinese shipment volumes measured in TEUs on US stock performance in the initial stages of the COVID-19 outbreak. The analysis indicates that, initially, US stocks were negatively affected irrespective of firms' trade engagements with China; however, as the global pandemic unfolded, companies with elevated imports from China exhibited more pronounced abnormal returns. The findings further reveal an increased influence of debt level and cash holdings on stock performance as the crisis intensified in Europe and the USA. These results highlight the evolving nature of global trade dynamics and their implications for financial markets amid global crises. Furthermore, this study provides valuable insights into the resilience of global supply chains during crises like the COVID-19 pandemic. The observed pattern, where companies with greater import volumes from China experienced better stock returns, underscores the importance of adaptable supply chains during disruptions. [ABSTRACT FROM AUTHOR]

The rapid increase in e-commerce and the emergence of combined passenger/freight systems in urban areas have raised the question of how best to integrate public transport services into door-to-door deliveries. This paper develops a variant of the pickup and delivery problem, called the two-echelon pickup and delivery problem using public transport (2E-PDP-PT). In the 2E-PDP-PT, the transportation network is split into two echelons. Different vehicles are utilized across the first and second echelons to ensure distribution efficiency. Parcels are delivered by public transport with free capacity or via trucks between satellites in the first echelon, and logistics vehicles are operated in the second echelon. The satellites are located at the echelon borders to transfer commodities between echelons. The 2E-PDP-PT aims to minimize total delivery costs and improve public transport capacity utilization. We formulate a new mathematical model based on a space-time network and adopt an adaptive large neighborhood search (ALNS) algorithm for the 2E-PDP-PT. The effectiveness of the ALNS algorithm is validated using newly generated small-scale instances. Furthermore, we investigate large-scale instances based on the Beijing Yizhuang transportation network. The computations show that an average total delivery cost savings of 4.5% is feasible. In addition, we analyze the impact of demand distributions and compare the ALNS algorithm and the LNS algorithm. Finally, we conclude that dynamically integrating public transport into freight transport services can benefit both logistics companies and public transport operators., Author(s): Shuai Wang [1]; Xiaoning Zhu [1]; Pan Shang (corresponding author) [1]; Wenqian Liu [1]; Xiao Lin [2]; Lóránt Tavasszy [2] 1. Introduction The substantial growth of e-commerce contributes to [...]

The delivery of goods (freight) accounts for the major cost and emissions in logistics systems worldwide. The effective management of the supply chain requires logistical efficiency and sustainability. Several logistics performance measurements such as distances driven and fuel efficiency are also indicators of sustainability. As an emerging paradigm, the Physical Internet (PI) addresses logistical, societal, and sustainability goals. However, the question remains whether some aspects of logistical efficiency in traditional logistics could be incorporated into the PI paradigm. To this effect, we examine how peddling, a consolidation strategy in traditional logistics, can enhance PI supply chain. Specifically, we formulate optimisation models and study the case of a Mexican automotive supply chain from both the PI and traditional logistics perspectives by comparing three different configurations; namely, Model P built on PI, Model S based on conventional standard peddling, and Model H, a hybrid. The hybrid Model H is optimised in a two-phase solution framework. We show via the case of a Mexican automotive supply chain that Model H outperforms others on average distance travelled and truck utilisation. Thereby, it is concluded that appropriate peddling and shipment consolidation policies may enhance PI supply chain logistics performance. [ABSTRACT FROM AUTHOR]

The growth of e-commerce has increased the number of home deliveries that need to be made in retail operations. Strategies such as reducing routing distance using optimisation models have been the most popular approaches to enhancing the efficiency of the delivery process and reducing its environmental burden. However, recently, customer purchasing behaviour has become relevant in understanding demand trends and increasing the effectiveness of the supply chain process. Customers are subject to different incentives to drive them to wait longer for their home deliveries. These incentives allow companies to pool and ship in more cost-efficient and energy-friendly alternatives. In this article, we present a methodology that uses a mixed-integer-linear programming model to evaluate the impact of extending delivery slots. We use real data from one of the largest retail companies in Mexico to analyse the impact of different time slot extensions for three different criteria: distance, transport costs and CO2 emissions. Our results show that the common approach of minimising distance is not recommended for any of the scenarios under study. On average, having up to 4 days for deliveries leads to savings of 57% in total distance, 61% in total costs and 56% in fuel consumption and/or CO2 emissions. [ABSTRACT FROM AUTHOR]