Pickup Customers Research Articles

Online Transportation Tariff Application (Maxim) In Padang City Revised from Islamic Business Ethics

The study was overturned by the fact that consumers who have used the maxim online transportation service in the rural city, where the consumer when using the service initially started its rates are changing and not in accordance with the initial booking. However, at the time the consumer has reached the target Maxim tariff rises for reasons given by the driver unknown. This type of research is a field research with the technique of interviewing stakeholders directly related to the issue the author discusses. Next to answer the problem formula, data in analysis with qualitative descriptive techniques. The result, suggests that in the implementation of the existing Maxim apalikation system in the field town, the initial tariff set by the maxim driver is not in line with the initial agreement. Initially before the pickup of consumers, the tariff was written on an application worth Rs 10,000 rupees, after the driver arrived at the customer pickup address, then the driver sent the consumer to the destination. After that, until the initial tariff of Rs 10,000 has changed to Rs 14,000. The Islamic business ethics review of the business behaviour of Maxim companies in Padang City is not in line with the Islamic ethics of business. It is a deceitful thing, which is the price or the price of the first order, when it has arrived.

A cooperative vehicle routing problem with delivery options for simultaneous pickup and delivery services in rural areas

The booming e-commerce is challenging express companies by requiring higher logistics service efficiency in rural China. This study investigates a cooperative vehicle routing problem for simultaneous pickup and delivery requests, in which the delivery orders can be fulfilled either by home delivery or customer pickup. The delivery option for each order is complex due to the optional cooperative relationships among express companies, the inter-dependence between self-pickup site selection and the overall online vehicle routing scheme, and the distance-dependent compensation to self-pickup customers. The problem is formulated as a mixed integer linear programming model and solved by a tailored adaptive large neighborhood search algorithm. A cost-saving allocation mechanism based on the core guaranteed Shapley value is applied to carrier collaboration. The numerical results show that the newly introduced cooperative distribution system can significantly reduce operational costs. Such improvements are robust even if the total demand changes or under different rural logistics network topologies.

Management of Online Transportation Services at the Gorontalo City Grab Office

The aim of this research is to find out the Management of Online Transportation Services at the Gorontalo City Grab Office. This research method is descriptive qualitative. Location: This research was conducted at the Gorontalo City Grab Office. The research results show that Management of Online Transportation Services at the Gorontalo City Grab Office. It can be seen from the results of the interview that the planning limits on the recruitment of new drivers are increasing every day to maintain a balance between drivers and customers. If drivers exceed customers, it will be increasingly difficult for drivers to get orders. It can be seen from the results of interviews that communication between drivers and customers often leads to misunderstandings, such as differences in customer pick-up or delivery locations, which leads to customers canceling orders. It can be seen from the interview results that Grab's supervision is still lacking for customers to maintain driver comfort. When there are individuals who violate the rules, especially customers who often make fictitious orders and cancel orders, this is detrimental to drivers.

Comparative analysis of modern digital services for the purchase of medicines

Currently, the online pharmacy market is represented by a number of large pharmaceutical players, including apteka.ru, eapteka.ru, and ozon.ru. Given the high density of the market, as well as the fact that medicines are commodities, it becomes obvious that the pharmacy brand needs to increase its competitiveness. Today, such factors are essential for the client of online pharmacies as: the ability to choose the best price offer, the availability of a large range of products, convenient search and comparison of drugs in various categories, as well as the possibility of delivery and customer pickup. Modern services for the search and purchase of medicines have a variety of capabilities that allow making the Internet service convenient for use, as well as to increase the competitive advantages of the pharmacy brand. Thus, the modern online pharmacy consumer is guided by a service (brand) that will satisfy his or her needs, including the use of cartographic services for a comfortable search.

A New Exact Algorithm for Single-Commodity Vehicle Routing with Split Pickups and Deliveries

We present a new exact algorithm to solve a challenging vehicle routing problem with split pickups and deliveries, named as the single-commodity split-pickup and split-delivery vehicle routing problem (SPDVRP). In the SPDVRP, any amount of a product collected from a pickup customer can be supplied to any delivery customer, and the demand of each customer can be collected or delivered multiple times by the same or different vehicles. The vehicle fleet is homogeneous with limited capacity and maximum route duration. This problem arises regularly in inventory and routing rebalancing applications, such as in bike-sharing systems, where bikes must be rebalanced over time such that the appropriate number of bikes and open docks are available to users. The solution of the SPDVRP requires determining the number of visits to each customer, the relevant portions of the demands to be collected from or delivered to the customers, and the routing of the vehicles. These three decisions are intertwined, contributing to the hardness of the problem. Our new exact algorithm for the SPDVRP is a branch-price-and-cut algorithm based on a pattern-based mathematical formulation. The SPDVRP relies on a novel label-setting algorithm used to solve the pricing problem associated with the pattern-based formulation, where the label components embed reduced cost functions, unlike those classical components that embed delivered or collected quantities, thus significantly reducing the dimension of the corresponding state space. Extensive computational results on different classes of benchmark instances illustrate that the newly proposed exact algorithm solves several open SPDVRP instances and significantly improves the running times of state-of-the-art algorithms. History: Accepted by Andrea Lodi, Area Editor for Design and Analysis of Algorithms–Discrete. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72222011, 71971090, 71821001, 72171112], by the Young Elite Scientists Sponsorship Program by CAST [Grant 2019QNRC001], and by the Research Grants Council of Hong Kong SAR, China [Grant 15221619]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/ijoc.2022.1249 .

THE LAST MILE DELIVERY PROBLEM: A KENYAN RETAIL PERSPECTIVE

The article aims to determine the last mile delivery challenges faced by online retailers in Kenya. This is based on the online retailing sub-sector’s contribution to the country’s economy. Despite its significant contribution to the country’s economy, little is known about the challenges facing online retailers during last mile delivery. In other countries such as China and South Africa, that are doing better in online retailing, extensive research has been done to determine unique challenges facing their online retailers during last mile delivery. It is important for the online retailers and relevant government agencies in Kenya to understand the last mile delivery factors that hinder the growth e-commerce. A qualitative research design using face-to-face interviews was used to collect data from seven online retail managers in Nairobi. The findings revealed there are a variety of last mile delivery challenges facing online retailers. These include the lack of a good national addressing system, traffic concerns, security concerns, high cost of delivery, postal service unreliability, and unconducive county government by-laws. The lack of a good national addressing system was found to be the most common last mile delivery challenge facing online retailers in Nairobi. It is recommended that retailers request their customers to share location details via online map applications such as Google Maps to overcome this challenge. The use of other delivery options, such as customer pick-up points of convenience can also be considered.

Intelligent Taxi Dispatch System for Advance Reservations

This research proposes and tests a new taxi dispatch policy to improve the existing systems used by taxi companies in Singapore. The proposed method chains trips made by reservations at least 30 minutes before the customer pick-up times. In this paper, the taxi dispatching system, Singapore Taxi Advance Reservation (STAR), is defined. A novel trip-chaining strategy based on a customized algorithm of Pickup and Delivery Problem with Time Window (PDPTW) is proposed. The idea is to chain several taxi trips with demand time points that are spread out within a reasonable period of time and with each pick-up point in close proximity to the previous drop-off location. The strategy proposed has the potential to lower the taxi reservation fee in Singapore to encourage advance reservations that facilitate trip chaining, which translates to lower taxi fares for customers, higher revenue for taxi drivers, and lower fleet ownership cost for taxi companies.

Multiple Drone Routing Problem for On-Demand Hyperlocal Market

Deploying drones for rapid pickup and delivery for on-demand customers in the hyperlocal market is unexplored in literature and demands attention. Maximizing customer pickup and deliveries with a limited drone flight endurance is essential but is hard to achieve in practice because of many service requests by on-demand customers. It mandates that drones cover extra mileage to visit docking stations in between services for recharge. Optimally allocating the services on available flight endurance and minimizing the docking station visits to complete all scheduled services is a predominant requirement for effective drone operations in a hyperlocal market. This problem is formulated as a mixed-integer linear programming model, and a heuristic algorithm is proposed to attempt various practical size problems, with near-optimal solutions reported. The paper offers valuable insights for practitioners and future researchers wishing to analyze the performance of drone operations and determine the appropriate number of drones required for the hyperlocal market based on service demand.

Hybrid and approximate algorithms for the dial-a-ride problem with adaptive ride times considering different service strategies

The dial-a-ride problem (DARP) is that of satisfying a number of pickup and drop-off customer requests, using a fleet of vehicles. In real life, traffic conditions can affect expected travel times, and hence the satisfaction of rigid pickup/drop-off time windows and scheduled ride times. This article considers the DARP with customer-adaptive ride times under different service conditions and strategies. The problem is formulated as a mixed integer linear programming model that minimizes service cost and customer inconvenience. A hybrid genetic–variable neighbourhood search algorithm (GAVNS) is proposed to solve the problem. Experiments are conducted to compare the performance of GAVNS with that of an approximate column generation algorithm, and to evaluate the application of different strategies on service efficiency and customer satisfaction. The results demonstrate the efficiency of GAVNS, and that limited violations of time-window and ride-time constraints can improve the service efficiency while preserving customer satisfaction levels.

A hyper heuristic for the green vehicle routing problem with simultaneous pickup and delivery

This paper studies the green vehicle routing problem with simultaneous pickup and delivery (G-VRPSPD). It aims to minimize fuel consumption costs while satisfying customer pickup and delivery demands simultaneously. The fuel consumption is directly proportional to green house gas emissions. We mathematically formulate the problem, and develop a hyper-heuristic (HH-ILS) algorithm based on iterative local search and variable neighborhood descent heuristics to effectively solve the problem. Extensive computational experiments are conducted to analyze the impact of the G-VRPSPD and the HH-ILS. We investigate the effect of green objective function on total fuel consumption cost by comparing the G-VRPSPD with the VRPSPD. We perform comparative analysis to investigate the performance of HH-ILS. We also conduct sensitivity analysis to investigate the performance of neighborhood structures, hyper heuristic and local search. The results show that the green objective function has a significant effect on total fuel consumption cost. The HH-ILS algorithm yields competitive results when compared with the mathematical formulation and the state-of-the-art heuristics in the literature.

A Location-Routing Problem with Market Competition for Designing Inland Port Urban Delivery Network

Wang, X.F. and Yang, F., 2020. A location-routing problem with market competition for designing inland port urban delivery network. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 333–338. Coconut Creek (Florida), ISSN 0749-0208.To effectively design an inland port urban delivery network for a logistics company, a nonlinear integer programming model for the location-routing problem with market competition (LRPMC) is presented. This problem seeks to construct an efficient logistics network to provide flexible and high quality delivery service for customers, so as to minimize operation cost, and maximize market shares. The logistics company can simultaneously provide two flexible delivery services: home delivery and customer pickup, and its market shares captured can be deduced from the patron behavior in competitive market. To solve the model, a hybrid heuristic algorithm combining genetic algorithm and local search is proposed. Based on the computational performances of real-world instance, the results show the proposed model formulation and heuristic approach are effective.

On the medication distribution system for home health care through convenience stores, lockers, and home delivery

Medication distribution service can be delivered based on a combination of home delivery and customer pickup. That is, medications are delivered either to customers' homes directly or to the pickup facilities (e.g. lockers) close to customers' homes. In Taiwan, there are more than 11,000 convenience stores that provide a 24-h service for customers to pick up the ordered items from e-commerce, which is unique to the world. In the medication distribution system, convenience stores can provide a unique opportunity for customers to more conveniently collect medications at stores, and also can reduce the operating cost for a logistics company providing the medication delivery service. Therefore, this work proposes a medication distribution system through convenience stores, lockers, and home delivery. Under this system, this work investigates how to simultaneously determine employment of convenience store chains, the convenience store locations to be visited, locations of lockers, vehicle routes for convenience stores and lockers, and vehicle routes for customers' homes, so that the total operating cost is minimized. This work further proposes a genetic algorithm to solve the medication distribution problem. Through simulation, the experimental results show that the proposed algorithm is able to solve the problem efficiently.

Internet shopping for Everyday Consumer Goods: An examination of the purchasing and travel practices of click and pickup outlet customers

The rapid spread of click and pickup outlets in France raises questions about the implications on shopping travel behaviours. The article seeks to measure the importance of online shopping for everyday consumer goods (ECG), and to understand offline purchases and travel behaviour of click and pickup customers. The research is based on a survey conducted in 2016 among approximately 600 French households. The profile of click and pickup customers is revealed by a logistic regression. Purchasing practices and the timing of shopping activities are comprehended from cross tabulation and chi-square tests. The results show that despite the widespread use of e-commerce, shopping ECG online remains a minority practice. Using click and pickup outlets allows customers to fine-tune their purchasing, both in terms of organising their time and the retail formats they use. It enables them to adopt diversified purchasing practices that are more in line with the households' schedules and consumption requirements. Our results show that households are still committed to traditional forms of retail, for which travel remains necessary. The implications of online shopping regarding the number of trips must therefore be seen in perspective, even if our findings reveal a reorganisation of shopping, particularly concerning time.

Uber: Applying Machine Learning to Improve the Customer Pickup Experience

Uber had pioneered the growth and delivery of modern ridesharing services by leveraging the explosive growth of technology, GPS navigation, and smartphones. Ridesharing services had expanded across the world, growing rapidly in the United States, China, India, Europe, and Southeast Asia. Even as these services expanded and gained popularity, however, the pickup experience for drivers and riders did not always meet the expectations of either party. Pickups were complicated by traffic congestion, faulty GPS signals, and crowded pickup venues. Flawed pickups resulted in rider dissatisfaction and in lost revenues for drivers. Uber had identified the pickup experience as a top strategic priority, and a team at Uber, led by group product manager Birju Shah, was tasked with designing an automated solution to improve the pickup experience. This involved three steps. First, the team needed to analyze the pickup experience for various rider personas to identify problems at different stages in the pickup process. Next, it needed to create a model for predicting the best rider location for a pickup. The team also needed to develop a quantitative metric that would determine the quality of the pickup experience. These models and metrics would be used as inputs for a machine learning.

Dynamic vehicle routing problem considering simultaneous dual services in the last mile delivery

PurposeThis paper aims to study the vehicle routing problem with dynamic customers considering dual service (including home delivery [HD] and customer pickup [CP]) in the last mile delivery in which three decisions have to be made: determine routes that lie along the HD points and CP facilities; optimize routes in real time, which mode is better between simultaneous dual service (SDS, HD points and CP facilities are served simultaneously by the same vehicle); and respective dual service (RDS, HD points and CP facilities are served by different vehicles)?Design/methodology/approachThis paper establishes a mixed integer linear programing model for the dynamic vehicle routing problem considering simultaneous dual services (DVRP-SDS). To increase the practical usefulness and solve large instances, the authors designed a two-phase matheuristic including construction-improvement heuristics to solve the deterministic model and dynamic programing to adjust routes to dynamic customers.FindingsThe computational experiments show that the CP facilities offer greater flexibility for adjusting routes to dynamic customers and that the SDS delivery system outperforms the RDS delivery system in terms of cost and number of vehicles used.Practical implicationsThe results provide managerial insights for express enterprises from the perspective of operation research to make decisions.Originality/valueThis paper is among the first papers to study the DVRP-SDS. Moreover, this paper guides the managers to select better delivery mode in the last mile delivery.

A branch-and-cut algorithm for the inventory routing problem with pickups and deliveries

This paper addresses the Inventory Routing Problem with Pickups and Deliveries (IRP-PD). A single commodity has to be picked up from several origins and distributed to several destinations. The commodity is made available at the supplier depot and at the pickup customers, with known amounts in each period of a discretized time horizon. The commodity is consumed by the delivery customers, whose demand, in each period of the time horizon, is known. The vehicles start and end their routes at the supplier depot. The objective is to determine a collection and distribution plan minimizing the sum of routing and inventory costs, satisfying inventory and capacity constraints. A mixed integer linear programming model is presented for the IRP-PD. Valid inequalities are proposed that are adapted from the inventory routing, the vehicle routing and the lot-sizing problems literature. Moreover, a new set of valid inequalities, called interval inequalities, is presented. A branch-and-cut algorithm is designed and tested on a large set of instances. Computational results show that the proposed approach is able to solve to optimality 946 out of 1280 instances. Moreover, the approach outperforms the state-of-the art method for the single vehicle case, increasing the number of instances solved to optimality from 473 to 538 out of 640 instances tested, with 133 new best known solutions.

A traveling salesman problem with time windows for the last mile delivery in online shopping

With the fast growth of the parcel volume of online shopping, home delivery (delivering parcels to customers’ homes or workplaces) has accentuated the pressure on last mile delivery actors. Customer pickup, which allows customers to pick up their parcels from shared delivery facilities near them, has become widely popular. This study introduces a novel travelling salesman problem with time windows for the last mile delivery in online shopping. The purpose is to find a minimum cost tour over given customers and/or shared delivery facilities (SDFs) in which unvisited customers are assigned to the SDFs. A general variable neighbourhood search heuristic is developed to solve the problem. Computational results corroborate that the proposed heuristic is competitive relative to well-known algorithms.

Real-world meeting points for shared demand-responsive transportation systems

While shared demand-responsive transportation (SDRT) systems mostly operate on a door-to-door policy, the usage of meeting points for customer pick-up and drop-off can offer several benefits, such as fewer stops and less total travelled kilometers. Moreover, real-world meeting points offer a possibility to select only feasible and well-defined locations where safe boarding and alighting are possible. This paper investigates the impact of using such meeting points for the SDRT problem with meeting points (SDRT-MP). A three-step procedure is applied to solve the SDRT-MP. Firstly, the customers are clustered into temporary and spatially similar groups and then the alternative meeting points, for boarding and alighting, are determined for each cluster. Finally, a neighbourhood search algorithm is used to obtain the vehicle routes that pass through all the used meeting points while respecting passengers’ time constraints. The goal is to examine the differences of a real-world meeting point-based system in contrast to a door-to-door service by a simulation with realistic meeting point locations derived from the map data. Although the average passenger travel time is higher due to increased walking and waiting times, the experiment highlights a reduction of operator resources required to serve all customers.

Measuring Spatial Accessibility to Pick-Up Service Considering Differentiated Supply and Demand: A Case in Hangzhou, China

In recent years, customer pick-up at collection and delivery points has become a popular alternative to traditional home delivery, which is under great pressure. However, current service of pick-up facilities has seldom been geographically evaluated despite its general uneven distribution and diverse needs. In this paper, in order to interpret the differentiation in customers’ service demands toward reception alternatives and in facilities’ service excludability in different built environments, a two-step floating catchment area (2SFCA) method is improved to measure customers’ spatial accessibility to pick-up facilities, providing a methodology to evaluate the match relation between the differentiated supply and demand of pick-up service. A case study of widespread automated parcel stations (APSs) is conducted in Hangzhou, China and correlative factors to residents’ accessibility are discussed. From the results, residents’ accessibility to pick-up service shows significant spatial unevenness and social inequity in the study area, which is found to correlate most to residences’ maintenance management. As well-managed, gated communities generally hold effective access to exclusive services, most open communities and self-built, single houses are in need of improvement due to inadequate service stemming from a high aging rate, lack of property management, and low service availability of nonexclusive facilities in open areas.

DESAIN JARINGAN DISTRIBUSI BERBASIS E-BUSINESS PADA SISTEM RANTAI PASOK

In this paper, we provide a form of distribution network design and application in the field of e-commerce in the supply chain, with a distribution network design approach. Thus a good distribution network model can be determined in e-commerce business and provide quality service through the delivery period of equipment and materials to the consumer's location that is fast and low cost which can provide more competitive prices for customers. This is where the role of distribution is very important, because with the distribution of all materials both raw materials and finished products can be distributed to each party in need in the supply chain. In the supply chain itself there are several distribution designs available, namely Manufacturer Storage With Direct Shipping, Manufacturer of Storage with Direct Shipping and In-Transit Merge, Storage With Carrier Delivery Distributor, Storage With Last-Mile Delivery Distributor, Manufacturer Or Distributor Storage With Customer Pickup.