Delivery Distance Research Articles

Penentuan Rute Terpendek Di Kantor Pos Kabupaten Blitar Dalam Pendistribusian Paket Menggunakan Algoritma Clarke And Wright Savings

Marketing strategy is a very important part in the execution of the overall corporate strategy, especially in a very tight competitor state. Route is a very important aspect considered by goods distribution companies. An effective and efficient distribution process is one of the factors whose conditions begin to align with other indicators in an effort to achieve customer satisfaction. The strategy that can be done is to involve calculating algorithms in contributing systematic and measurable solutions. The Clarke and Wright Savings algorithm is an effective method in determining the shortest route of distributing goods, because the Clarke and Wright Savings method has its own heuristics which make savings in the form of mileage or distribution time. This study aims to determine the shortest route at the Blitar checkpoint post office (KPRK) in distributing express service type bags to each branch post office point (KPC) using the Clarke and Wright Savings Algorithm. The results of the discussion on the application of the Clarke and Wright Savings method to determine the shortest route for the service bag distribution fleet from the KPRK Blitar post office to KPC can be concluded that, there are two initial routes owned by the company with a total delivery distance of 189.7 km. After calculation, two routes with the shortest distance will be traveled with a total delivery distance of 171 km. Route group 1 is Blitar Post Office à KPC Garum à KPC Nglegokà KPC Gandusarià KPC Talun KPC Wlingi à KPC Doko à KPC Kesamben à KPC Selopuroà KPC Binangun à KPC Kanigoro à KPC Lodoyo à KPC Kademangan à Post Office with a distance of 116.7 km. As for route 2, namely the blitar post office à KPC Sanan Kulon à KPC Ponggok à KPC Srengat à KPC Kademangan à KPC Udanawu à Blitar post office with a distance of 54.3 km. With the establishment of routes with the closest distance, the company can save mileage by 9.85%.

Modeling the online food delivery pricing and waiting time: Evidence from Davis, Sacramento, and San Francisco

The proliferation of delivery services has increased researchers' and practitioners' interest in understanding their potential impacts on urban mobility. While there have been studies focusing on the operations and management of such services, there is a lack of understanding about the quality of the delivery service and their pricing schemes. In this empirical study, we examine the delivery fee and wait time variations for ordering food using four food delivery applications in the U.S.: DoorDash, Grubhub, Postmates, and Uber Eats. We collected delivery data featuring a variety of attributes of cost, timing, restaurant type, and location. The analyses cover all pricing items comprising total cost across the apps and various study areas. Furthermore, we estimated mixed-effect ordered-logistic regression (ologit) models to identify the variables and assess their association with food delivery fees and wait times. Results revealed that delivery fee variation across time of day or day of the week is negligible; however, delivery distance significantly influences delivery fees, and this effect varies considerably across apps. The observed effect of requester location reveals potential zone-based delivery pricing schemes by apps. Delivery wait time is shorter when demand and supply are high. Platforms with more established networks of users and couriers feature shorter wait times. The results of this study provide insight into user experiences with food delivery services and the choices available, which can help inform the development of pricing schemes for food delivery; the development of better optimization and operations management strategies by incorporating knowledge of key variables.

Utilization of the secondary resources of titanium-zirconium pits when constructing highways

Purpose. To develop a methodology for determining the economically feasible distance of construction sand haulage, which is a secondary raw material of ore pits, to highway construction sites in comparison with the delivery of sand from mining enterprises of building materials, taking into account land conservation indicators. Methodology. The research used a set of methods: analytical method – to establish the main technical and economic indicators that affect the cost of delivering sand from the mining enterprises to the road construction site; technical and economic analysis – to determine the influence of the building materials haulage distance on the cost of construction works. Findings. The economically permissible haulage distance for sands form titanium-zirconium mining enterprises to highway construction objects was established in comparison with the involving of sands from deposits of building materials. It has been proven that under the conditions of using the sands of the Motronivskyi MPP, where the main raw material is titanium-zirconium ores, in addition to the economic effect of the mining waste disposal, there is an ecological effect of reducing the dumps and tailings areas. At the same time, the cost of sand rocks during the construction of the road surface will be reduced by 3 to 60 %, depending on the distance to the construction road site. All together, the area of lands saved from being disturbed by new mining operations will reach 3.3 hectares during the construction of a 2.5 km long category I-b road section. Originality. Dependence was established of the sand cost and its delivery to the object of new highway construction on the materials haulage distance when purchasing sand at the enterprise of the main raw material and from the titanium-zirconium deposit, where it is developed as an associated raw material. The dependence of the economic efficiency indicator of the road construction on the increasing distance of sand rocks delivery from the titanium-zirconium deposit was determined, which allows justifying the rational haulage distance according to technical and economic indicators. Practical value. The developed method for determining the effective haulage distance for sand rocks to the construction site allows one to calculate the expediency of involving associated minerals of ore pits during the reconstruction and construction of new highways, as well as to establish the effect of resource conservation due to the reduction in the area of mining facilities during the extraction of ore and building raw materials.

A flexible cost model for seaport-hinterland decisions in container shipping

A seaport–hinterland system offers a wide range of service options for shippers and consignees to export or import containerized cargo. The present study, set within the context of Brazil, seeks to propose a flexible cost model to aid joint seaport–hinterland network decisions by freight forwarders and clients. More specifically, employing simulation and sensibility analysis, the proposed model is employed to explore: (i) decisions on whether to perform logistics services in seaports or dry ports; (ii) decisions on whether to transport containerized cargo by road or by multimodal transportation (road and rail); and (iii) decisions on whether cargo is best delivered or received in either consolidated or deconsolidated form. Simulations are undertaken against seven transportation strategy permutations via which service operators might deliver containers from seaports or dry ports to clients. We find five factors—(i) cargo value, (ii) cargo accommodation type, (iii) transportation mode, (iv) delivery distance and (v) shipping process time—as critical to joint seaport–hinterland operations impacting shippers and consignees. Furthermore, dry ports are shown to be particularly cost efficient for imports requiring long-term storage, even where the dry ports are not directly connected to seaports or intermodal facilities.

Remote Evidence-Based Health Promotion Programs During COVID: A National Evaluation of Reach and Implementation for Older Adult Health Equity.

Evidence-based health promotion programs (EBPs) support older adults where they live, work, pray, play, and age. COVID-19 placed a disproportionate burden on this population, especially those with chronic conditions. In-person EBPs shifted to remote delivery via video-conferencing, phone, and mail during the pandemic, creating opportunities and challenges for older adult health equity. In 2021-2022, we conducted a process evaluation of remote EBPs by purposively sampling diverse U.S. organizations and older adults (people of color, rural, and/or with disabilities). The Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) + Equity framework was used to understand program reach and implementation, including FRAME to describe adaptations for remote delivery. Analyses include descriptive statistics and thematic analysis of participant and provider surveys and interviews, and joint display tables to compare learnings. Findings from 31 EBPs through 198 managers/leaders and 107 organizations suggest remote delivery increases EBP reach by improving access for older adults who are underserved. For programs requiring new software or hardware, challenges remain reaching those with limited access to-or comfort using-technology. Adaptations were to context (e.g., shorter, smaller classes with longer duration) and for equity (e.g., phone formats, autogenerated captioning); content was unchanged except where safety was concerned. Implementation is facilitated by remote delivery guidelines, distance training, and technology support; and hindered by additional time, staffing, and resources for engagement and delivery. Remote EBP delivery is promising for improving equitable access to quality health promotion. Future policies and practices must support technology access and usability for all older adults.

Model test based study on icing process of long-distance water channel operating at low temperature environment

The icing problem seriously affects the efficiency of channel water delivery in low temperature conditions. A low-temperature and long-distance channel model test platform was established to study the icing process. Through this model test platform, water temperature and formation of ice cover were tested and discussed. Furthermore, the relationship between border ice width and its influencing factors were studied quantitatively. The test results show that through the recirculating flume at a negative temperature environment, the model test platform can simulate the icing process under a long-distance water delivery situation. The water temperature decreases with the increase of delivery distance and operating time. The formation of ice cover begins from the growth of border ice; however, the static formation of ice cover is rapid, but the dynamic formation of ice cover shows an obvious process of border ice lateral growth. An equation for border ice width and ice concentration was established for prediction.

AB-453068-4 BENCH EVALUATION OF OVERLAPPING LESION STEAM POP RATES

Sequentially delivered, overlapping radiofrequency (RF) ablation lesions pose a risk of creating steam pops due to heat stacking. The relationship between inter-lesion distance and heat stacking is presently unknown. Therefore, the smallest inter-lesion distance for safe therapy delivery needs to be determined. The study objective was to quantify steam pop rates when creating sequential, adjacent, potentially overlapping RF ablation lesions at various inter-lesion distances in a non-perfused bovine cardiac tissue model with the intention of identifying the safest minimum inter-lesion distance. In a saline filled tank at clinically relevant conductivity and temperature, a TactiCath SE RF ablation catheter created sets of 2 lesions on isolated, non-perfused bovine right ventricular tissue. At 15g force and 40W, successive 10s lesions were created (transition time less than 1s between lesions) at center-to-center distances of 1, 2, 3, 4, 5, and 10 mm, and steam pop frequency was determined. If a steam pop occurred during the first 10s lesion prior to the drag, the trial was excluded and repeated. Using pilot data, it was determined a minimum of 49 samples at each inter-lesion distance would provide a robust sample size for statistical analysis. Steam pop rate at an inter-lesion distance of 10mm was used as the control for analysis as there was no lesion overlap at this center-to-center distance. Steam pop rates at 1 and 2 mm were significantly greater (p=0.002 and p<0.001) than at 10mm. Using a 2-proportions, 2-sample non-inferiority (NI) test, with a NI margin of 20%, statistical equivalence was claimed between steam pop rates at 10mm and 5mm (p=0.009), 4mm (p=0.005), 3mm (p=0.003). Lesions spaced closer than 3mm apart have a greater risk of resulting in steam pops. Therefore, a minimum of 3mm inter-lesion distance would be recommended as it has shown to have a similar steam pop rate to focal lesions.

Multi-Location Assortment Optimization with Drone and Human Courier Joint Delivery

This paper studies the constrained multi-location assortment optimization problem under joint delivery by drone and human courier. To maximize the revenue of the retailer, product assortment and last-mile delivery methods are configured simultaneously. To handle the joint delivery problem with product assortment, a mixed multinomial logit model is established to depict the customer purchase behavior. We also take into account the load capacity of drones and the delivery distance limit of drones and human couriers. To the best of our knowledge, the present paper is the first to study the assortment optimization problem considering joint delivery by drone and human courier. The problem is first formulated as a mixed-integer linear programming (MILP) model, which is then transformed into a conic quadratic mixed-integer model with McCormick inequalities (Conic + MC). In the numerical study, it is demonstrated that Conic + MC outperforms MILP as Conic + MC finds the optimal solution within 300 s, while MILP needs more than 600 s. Furthermore, several management insights are revealed for retailers regarding assortment planning when facing different kinds of product revenue structures, and advice is provided for online ordering platforms in terms of setting delivery limits.

Research on Demand-Based Scheduling Scheme of Urban Low-Altitude Logistics UAVs

Aiming at the problem of the scheduling scheme of urban low-altitude logistics unmanned aerial vehicles (UAVs), this paper establishes a demand-based UAV scheduling scheme model using an improved simulated annealing algorithm, taking minimizing the cost of distribution as the objective function and considering restrictions such as UAV performance constraints, airspace constraints, and distribution constraints, among others. For verification, actual express data and airspace constraints in Shanghai are taken as examples. Two urban air traffic networks are constructed using road and building data. The analysis results show that the planning scheme of this model is superior to other forecasting models in terms of delivery cost and delivery time. In addition, this model can flexibly calculate the optimal scheduling scheme under the constraints of multiple parameters, according to the requirements of delivery volume, delivery distance, UAV performance, etc.

Incentive mechanism and path planning for Unmanned Aerial Vehicle (UAV) hitching over traffic networks

Package delivery via the Unmanned Aerial Vehicles (UAVs) is a promising transport mode to provide efficient and green logistic services, especially in urban areas or complicated topography. However, the UAV’s limited energy storage makes it difficult to perform long-distance delivery tasks. In this paper, we propose a novel multimodal logistics framework based on crowdsourcing, in which the UAVs can call on ground vehicles to provide hitch services for energy saving and extending their delivery distance. This multimodal logistics framework is formulated as a two-stage model to jointly consider the incentive mechanism design for crowdsourced ground vehicles and path planning for UAVs. In Stage I, to deal with the motivations for ground vehicles to assist UAV delivery, a dynamic pricing scheme is proposed to best balance the vehicle response time and payments to ground vehicles. It shows that a higher price should be decided if the vehicle response time is long to encourage more vehicles to offer a ride. In Stage II, the task allocation and path planning of the UAVs over the traffic network is studied on the basis of the vehicle response time obtained in Stage I. To address pathfinding with restrictions and the performance degradation of the pathfinding algorithm due to the rising number of conflicts in multi-agent pathfinding, we propose the suboptimal conflict avoidance-based path search (CABPS) algorithm, which has polynomial time complexity. Finally, we validate our results via simulations. It is shown that our approach is able to increase the success rate of UAV package delivery. Moreover, we estimate the delivery time of the UAV in a pessimistic case, it is still twice as fast as the delivery time of the ground vehicle only.

Multi-Objective Scheduling Strategy of Mine Transportation Robot Based on Three-Dimensional Loading Constraint

In an attempt to solve the problems of the low intelligent distribution degree and high working intensity of auxiliary transportation systems in underground coal mines, an intelligent distribution strategy of materials in the whole mine is put forward. Firstly, combined with the characteristics of materials and standard containers, a three-dimensional loading model is established with the goal of maximizing the space utilization of standard containers, and a three-dimensional space segmentation heuristic algorithm is used to solve the material loading scheme. Then, the multi-objective optimization model of distribution parameters is established with the goal of the shortest delivery distance, the shortest delay time, and the fewest number of delivery vehicles, and the dual-layer genetic algorithm is used to solve the distribution scheme. Finally, the spatiotemporal conversion coefficient is designed to solve the task list by hierarchical clustering, and the solution time is reduced by 30%. The results show that the dual-layer genetic algorithm based on hierarchical clustering has good adaptability in complex material scheduling scenarios.

Production Inventory Optimization Considering Direct and Indirect Carbon Emissions under a Cap-and-Trade Regulation

Background: The latest global agreement on net-zero emissions encourages new studies on production inventory optimization that promote carbon emissions reduction without harming a company’s profit performance, particularly because certain carbon-pricing regulations bind manufacturing companies. Methods: This study aims to develop a production inventory model that considers direct and indirect emissions in three emission scopes. It incorporates emissions from production, material handling, transportation, and waste disposal for further treatment under a carbon cap-and-trade regulation. With the help of Maple software, a convex total cost function was solved. Results: The results show that the optimum production quantity depends on the values of demand, setup cost, holding cost, fixed cost per delivery, fixed cost for waste disposal, and other parameters related to carbon prices. This study also found that the total cost was highly dependent on the values of the carbon cap, carbon price, and delivery distance. Meanwhile, changes in the delivery distance and fuel emissions standard significantly impacted total emissions. Conclusions: The proposed model can guide manufacturing companies in setting the optimum production quantity per cycle. Moreover, they must carefully manage the delivery and setting of the carbon cap and carbon price from the government.

The evaluation of N/P fate using the SPARROW model: a case study in an arid and semi-arid region, northern China.

The assessment of nutrients' fate from source to sink is critical to water quality control. As an important ecological reserve in the arid and semi-arid regions of China, the Luanhe River Basin (LRB) has suffered from the deterioration of water quality, thus leading to the urgent management and control. However, few studies have devoted to exploring the fate of N/P contaminations for the entire watershed, due possibly to the large drainage area and heterogeneous watershed composition. Here, we attempt to illustrate N/P contaminations delivery and retention processes using the SPAtially Referenced Regression On Watershed attributes (SPARROW) model. The model reveals 97% of the spatial variability in the TN load and 81% in the TP load, verifying its availability and credibility. The results indicate that anthropogenic sources are dominating the N/P load, which account for 68.5% of N and 74.6% of P inputs. The results highlight the significant retention effects of streams and reservoirs, with 16.4% of N and 13.4% of P removals by streams and 24.3% of N and 10.7% of P removals by reservoirs, respectively. Ultimately, only 49,045.2 t yr-1 (or 16.9%) of N and 1668.7 t yr-1 (or 17.1%) of P being transported to the Bohai Sea. In addition, the analysis of influencing factors showed that regional characteristics (e.g., topography, rainfall), stream size, and delivery distance are potential factors affecting the riverine transport, whereas flow rate and surface area are primarily affecting the reservoirs attenuation. In the future, the watershed water quality management should pay more attention to source management and pollution legacy risks to achieve sustainable and healthy watershed development.

Fuzzy-Logic Approach to Estimating the Fleet Efficiency of a Road Transport Company: A Case Study of Agricultural Products Deliveries in Kazakhstan

The estimation of the efficiency of road transport vehicles remains a significant problem for contemporary transport companies, as numerous stochastic impacts, such as demand stochasticity, road conditions uncertainty, transport market fluctuations, etc., influence the technological process. A fuzzy-logic approach is proposed to consider the uncertainty relating to estimating vehicle fleet efficiency. According to the developed approach, vehicle efficiency is described based on a membership function, whereas the efficiency of the whole vehicle fleet is evaluated as a fuzzy set. To demonstrate the developed approach, a case study is depicted for using cargo vehicles to deliver agricultural products in the Republic of Kazakhstan. The numeric results are presented for the selected models of vehicles that a transport company uses to service a set of clients located in Northern Kazakhstan: the transport services provided for each of the clients are characterized by numeric demand parameters—the consignment weight and the delivery distance. The completed calculations allowed us to obtain the membership functions for the alternative vehicle models and to present the transport company’s vehicle fleet as a fuzzy set.

Advancing the marketing‐operations interface in omnichannel retail

Advancing the marketing‐operations interface in omnichannel retail

Fleet Design Optimization of Package Delivery Unmanned Aerial Vehicles Considering Operations

The conceptual design process of aircraft starts by deciding the representative mission requirements, followed by optimization of design variables to satisfy the given requirements. However, the appropriate mission requirements are not obvious, especially when designing package delivery unmanned aerial vehicles (UAVs; also called drones). The UAVs must accommodate various combinations of package weights and delivery distances. The complexity increases further when designing a heterogeneous fleet of UAVs that serves a large number of customers. This work addresses this problem by solving coupled design–operation optimization to find optimal mission requirements and optimal UAV designs simultaneously. We formulate this problem as a mixed-integer nonlinear optimization and propose a sequential heuristic algorithm to solve the coupled problem. The benchmark study of the proposed algorithm against a nonconvex branch-and-cut solver shows that the sequential heuristics are effective. We also demonstrate that the simultaneous UAV design and routing optimization reduces the UAV weight across the fleet by more than 12% on average compared to the conventional baseline.

Environmental profile of 3D concrete printing technology in desert areas via life cycle assessment

Three-dimensional concrete printing (3DCP) offers a particularly advantageous construction method in harsh environments, such as desert areas that experience shortages of building materials and labor. Evaluating the environmental impacts of 3DCP in remote areas is essential for substantification and thus practical application of this technology. Therefore, life cycle assessment against conventional construction was conducted in this study to determine the environmental profile of 3DCP in desert areas considering different reinforcement methods and aggregates. The comparison results indicate that 3DCP is more sustainable owing to its lower potential for freshwater ecotoxicity, particular matter formation, human toxicity, ozone depletion, and eutrophication. The environmental friendliness of using in-situ desert sand for 3DCP depends on the material delivery distance. Electricity consumption also influences the environmental impact of 3DCP. Although 3DCP is promising as an environmentally friendly construction method for use in remote areas, technological updates and energy supply adjustment and justification remain essential.

Modeling of Transport Problem in Linear Programming with Python (PULP)

Integer programming is a framework for rapid conversion and global optimum. The basic issue in transportation problem is to minimize the cost or time (distance) of delivery. There are two things in our consideration, one is cost of transportation and other demand or how much can be supply. This paper will discuss the transportation problem and apply the zero-one integer assignment to reduce the complexity of the transportation solving concept. The paper will develop the concept to solve the transportation problem and apply the zero-one integer to find the optimum cost of transportation. This paper convert transportation problem in integer programming than solve with machine learning. The paper will present a model of transportation problem solution with the PULP software. We will introduce the programming in Python to make a model to minimize the cost (time or distance) in any transportation problem and Mathematical algorithm of zero-one Transportation programming to solve these types of problems.

Choice of a logistics route for cargo delivery in modern conditions

The current conditions of the global movement of goods under sanctions make it necessary to build new logistics routes along those international transport corridors that will ensure the reliability of transportation. Crisis points in any industry are at the same time a potential for development and growth, which is confirmed by the history of the development of logistics in the XX century. Basic principles of logistics and methods of quality management theory should serve as a basis for choosing the vector of transport and production development. Transit potential of the Russian Federation is unlocked by the Northern Sea Route, latitudinal corridor “East-West” and meridional corridor “North-South”. Tough policies of some countries make it necessary to redirect commodity flows along new logistic routes. The analysis of goods traffic promotion through the North-South corridor shows its serious competitive advantages in comparison with the Southern sea route in terms of transportation distance, time, and cost of delivery. The study analyzes the problems of the international transport corridor. These include technological, documentary, and infrastructural unresolved problems. The multivariant logistic route in the central part of the North-South corridor poses the problem of choosing the optimal route. The article analyzes the existing methods of route choice based on equal advantageous transportation distance and full cost for solving this task. The limitation of the listed methods leads to the search for a cost minimization function for a logistics route.

Research on delivery problem based on two-stage multi-objective optimization for takeout riders

From the perspective of takeout riders, in order to ensure the safety of riders, reasonably arrange the distribution tasks of riders and improve the distribution efficiency of the platform, this paper proposes a new distribution mode. In the future, efficiency is the core competitiveness of the takeout platform, and humanization is an important condition for the long-term development of the takeout platform. Both are indispensable. This paper simplifies the traditional many to many distribution mode into one to many distribution mode, and realizes the new distribution mode through two-stage multi-objective optimization algorithm. In the first stage, genetic algorithm is applied to analyze and optimize the new distribution mode for the first time; In the second stage, the large-scale neighborhood search algorithm is applied to destroy and reorganize the distribution route obtained in the first stage according to the objective function to obtain the optimal distribution route. Aiming at the three scenarios of consumer group distribution generated by random simulation, high-density and low-density consumer group distribution in Shenyang, this paper uses MATLAB tools to simulate. Through the analysis of simulation results, the working hours and delivery distances of takeout riders are reduced, and the maximum delivery volume is limited. So the method proposed in this paper can not only improve the intelligent level of distribution, but also propose a more humanized distribution mode from the perspective of takeout riders, which greatly supports the sustainable development of the delivery system of network connected takeout platform.