Pick-up Stations Research Articles

A fast simulated annealing heuristic for the multi-depot two-echelon vehicle routing problem with delivery options

ABSTRACT We studied a variant of the vehicle routing problem (VRP) arising in last-mile distribution, called the multi-depot two-echelon vehicle routing problem with delivery options (MDTEVRP-DO). The MDTEVRP-DO involves two decision levels: (i) designing routes for a fleet of vehicles located in multiple depots to transport customer demands to a set of satellites and (ii) routing a fleet of vehicles from the satellites to serve the final customers. Nowadays, a relevant feature of the problem characterizing delivery services is that customers can collect their packages at pickup stations near their homes or workplaces. We designed an effectively simulated annealing (SA) heuristic for the problem. The new algorithm was extensively tested on benchmark instances from the literature, and its results were compared with those of start-of-the-art algorithms. The results show that the proposed SA obtains 30 out of the 36 best solutions for the MDTEVRP-DO benchmark instances. Moreover, its computation performance is superior to state-of-the-art algorithms for the MDTEVRP-DO.

Planning of reliable targeted evacuation under the threat of disasters

In planning evacuation services against the threat of disasters, it is important to optimize pickup point location and rescue vehicle routing decisions while recognizing the risks of service disruptions. In this paper, a reliable location and routing model with backup service plans is proposed to plan targeted strategic evacuation, which minimizes the total expected cost for deployment of pickup stations, rescue vehicle routing, and evacuee assignments and exposure while the service is subject to probabilistic disruptions. We formulate the problem as a mixed-integer non-linear program, and develop two customized solution algorithms, one based on Lagrangian relaxation (LR) and the other based on meta-heuristic, to decompose and solve the problem. Numerical experiments with various parameters are conducted to not only demonstrate the applicability of the proposed model and effectiveness of the solution algorithms, but also to draw managerial insights. The impacts of demand distribution, facility cost, disruption probability, and evacuee exposure risk are assessed in a series of sensitivity analyses, so as to inform agencies how to carefully consider these factors while developing a reliable targeted evacuation service plan.

Multitrip vehicle routing with delivery options: a data-driven application to the parcel industry

To make the last mile of parcel delivery more efficient, service providers offer an increasing number of modes of delivery as alternatives to the traditional and often cost-intensive home delivery service. Parcel lockers and pickup stations can be utilized to reduce the number of stops and avoid costly detours. To design smart delivery networks, service providers must evaluate different business models. In this context, a multitrip vehicle routing problem with delivery options and location-dependent costs arises. We present a data-driven framework to evaluate alternative delivery strategies, formulate a corresponding model and solve the problem heuristically using adaptive large neighborhood search. By examining large, real-life instances from a major European parcel service, we determine the potential and benefits of different delivery options. Specifically, we show that delivery costs can be mitigated by consolidating orders in pickup stations and illustrate how pricing can be applied to steer customer demand toward profitable, eco-friendly products.

Interrogating the Myths of Education: Dorothy Bryant'sElla Price's JournalandMiss Giardino

Interrogating the Myths of Education: Dorothy Bryant's<i>Ella Price's Journal</i>and<i>Miss Giardino</i>

Large-scale dockless bike sharing repositioning considering future usage and workload balance

Dockless bike sharing (DBS) has the free-floating feature and large-scale fleet, which poses significant challenges to repositioning. This paper finds the Matthew mechanism of bike floating based on real-world trip data in Nanjing, China, and then proposes an integrated method for the large-scale DBS repositioning problem. Firstly, trip origins are analyzed by the first layer clustering to identify thousands of virtual stations. Secondly, the novel index of bike density and turnover rate are used in target inventory estimation for higher future usage. Lastly, the second-level clustering algorithm assigns workload-balanced tasks to truck drivers, and an advanced neighborhood search algorithm is applied to design the truck route. Results show that there are about three hundred pick-up stations and about three thousand drop-off stations for Nanjing DBS repositioning. And the proposed method is demonstrated to provide a better solution for increasing future usage and improving driver workload balance.

A branch-and-price algorithm for location-routing problems with pick-up stations in the last-mile distribution system

In catering to the needs of the growing e-commerce demand and environmentally friendly urban delivery solutions, package delivery companies are increasingly focusing on user experience and sustainable operations, such as alternative delivery methods (e.g., pick-up stations) and green delivery vehicles (e.g., electric vehicles). We consider designing a location-routing problem with pick-up stations (LRP-PS) where the location of pick-up stations to open and the delivery plan of green vehicles (GVs) are optimized simultaneously. The purpose is to satisfy the total demand while minimizing the sum of opening cost and handling cost of pick-up stations and the fixed cost and routing cost of GVs. Then, we present a compact mixed-integer programming formulation to define the LRP-PS and reveal some interesting properties of the optimal solution. We propose an effective branch-and-price (B&P) algorithm to solve the LRP-PS, which is demonstrated to outperform greatly commercial branch-and-cut solvers such as CPLEX in the computational study. Finally, through a comprehensive analysis of several key parameters (e.g., coverage ranges of pick-up stations and battery driving ranges of GVs), we assess the impact of pick-up stations on this last-mile distribution system and provide some helpful business insights for package delivery companies.

Pickup and delivery problems with autonomous vehicles on rings

In this paper we introduce a new class of Pickup and Delivery problems on circles (or rings). These problems arise in the field of public transportation systems where autonomous (i.e. driverless) vehicles travel on circular networks. We consider a set of stations arranged in a circle and a set of transportation requests. Each request asks for the transportation of a certain quantity from a pickup station to a delivery station. A fleet of capacitated vehicles is available at the depot. In the first part of the paper we propose a classification scheme for these problems. In the second part, we address the variants in which the vehicles are allowed to move in a single direction of the circle (either clockwise or counterclockwise) and the objective is to minimize the number of tours on the ring while serving all the requests. We provide a complexity analysis for this class of problems. We develop polynomial time algorithms for the variants that are polynomially solvable and proofs of NP-hardness for the variants that are NP-hard. In addition, for the latter, we provide mathematical formulations and perform computational tests that show the effectiveness of these formulations. Finally, we compare optimal solutions with those obtained using a straightforward greedy algorithm.

Repositioning Shared Urban Personal Transport Units: Considerations of Travel Cost and Demand Uncertainty

Operators of personal transport units (PTUs) face the challenge of intelligently balancing the locational demand and supply of PTUs in order to mitigate surpluses or deficits at PTU pickup stations. To accomplish this goal, operators need to be able to reliably predict the spatial distribution of PTU demand and to optimize the distributional allocation of resources to meet this demand. This paper proposes a three-step mathematical programming approach that addresses PTU supply vehicle routing and PTU repositioning that minimize the weighted total travel costs and unmet user demand. The methodology combines discrete wavelet transform (DWT) and artificial neural network (ANN) techniques to predict the demand at PTU stations, considers travel cost and unmet user demand in a multiobjective model and solves it with a multiobjective coevolutionary algorithm (MOCA), and incorporates the demand uncertainty to ensure robustness of the optimal repositioning and routing strategy for all the PTU stations. The paper demonstrated the proposed approach using real-world bicycle-sharing data from Nanjing, China, and showed that the proposed approaches for demand prediction (DWT-ANN) and optimization (MOCA) significantly produce superior results compared with traditional methods. Sensitivity analysis demonstrated the robustness of the proposed approaches.

Time and Cost Efficiency of Autonomous Vehicles in the Last-Mile Delivery: A UK Case

In recent years, last-mile delivery has become an increasingly important area in the global supply chain. Practically, there has been an increasing worldwide interest in developing the last-mile delivery robots/vehicles to increase the efficiency of the whole supply chain. Theoretically, several researchers have suggested that using autonomous robots brings more efficiency for delivery. However, almost no current studies consider a specific last-mile delivery activity &amp;ndash; transport from supermarkets after loading to pick-up stations before unloading. The goal of this study is to investigate whether and how autonomous vehicles/robots can address the issue of cost and time efficiency. Specifically, this research aims at identifying the time and cost structures of using autonomous vehicles for the delivery along the chosen route &amp;ndash; a single way from the Sainsbury&amp;rsquo;s supermarket to the Amazon pick-up station at Coventry. Furthermore, the research aims to find whether using autonomous vehicles is more efficient in time and/or cost than using vans with drivers for this route.

Sizing of a homogeneous fleet of robots in a logistics warehouse

Abstract We are interested in the problem of determining the size of a fleet of robots able to perform transport operations in a logistics warehouse. The operations are divided into several phases: loading, loaded travel, unloading and empty travel. We first determine the minimum number of robots needed to transport a set of homogeneous loads from point A to point B over a determined time interval. For the same number of robots, many assignments exist. We determine the assignment that minimizes the makespan, which is also the one which balances the loads between robots. If we consider an infinity of pickup stations, we obtain a simple analytical expression to find the optimal number of robots. With a single pickup station, we present a simple algorithm that computes the optimal fleet size. Finally, we show that the extension with heterogeneous loads can be formulated as a bin packing problem.

Disruption of HIV Service Provision and Response in Hong Kong During COVID-19: Issues of Privacy and Space.

The impact of the COVID-19 pandemic on sexual and reproductive health and rights is a significant public health issue. HIV/AIDS related services have been severely disrupted during the pandemic in different aspects. This paper highlights how privacy concerns affected HIV service provision during COVID-19 in Hong Kong, by sharing the experience of AIDS Concern Hong Kong. Based on our experience of working with our local MSM clients, temporary closure of center-based testing, venue-based testing in gay saunas, and mobile testing, meant that MSM could not easily go to a safe space to get anonymous and gay-friendly testing. To mitigate this, AIDS Concern Hong Kong put effort into promoting and making self-testing available during periods of testing center closure. We also made sure that people can choose to have test kits delivered to an anonymous pick-up station.

Same-Day delivery with pickup stations and autonomous vehicles

Same-day delivery has become a very important challenge for e-commerce providers. However, effective delivery concepts are still not established. In this paper, we analyze the potential of combining parcel pickup stations and autonomous vehicles for same-day delivery. This combination may allow for consolidation of goods, automated delivery processes, and reduced operation costs. We consider the problem on the operational planning level. A depot, a set of pickup stations, and an autonomous delivery fleet are given. Customers dynamically order goods to a preferred pickup station and expect fast service. The goods need to be delivered from the depot to the preferred pickup station or another pickup station in the close neighborhood. Autonomous vehicles are directly dispatched between the depot and the stations. To decide where and when to dispatch a vehicle and about the corresponding goods to load, we present a policy function approximation (PFA). Our intuitive PFA allows real-time decision making while balancing the tradeoff between fast delivery and consolidation. We conduct an extensive computational study for the pickup station network of the city of Braunschweig. We show how our delivery concept allows fast delivery for up to 100 delivered goods per vehicle and day. We further pair the PFA with a value function approximation to account for heterogeneity in demand. We finally derive important managerial insights for strategical and tactical planning and present an extensive outlook on promising future research directions.

Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach

This work proposes a persuasion model based on argumentation theory and users’ characteristics for improving the use of resources in bike sharing systems, fostering the use of the bicycles and thus contributing to greater energy sustainability by reducing the use of carbon-based fuels. More specifically, it aims to achieve a balanced network of pick-up and drop-off stations in urban areas with the help of the users, thus reducing the dedicated management trucks that redistribute bikes among stations. The proposal aims to persuade users to choose different routes from the shortest route between a start and an end location. This persuasion is carried out when it is not possible to park the bike in the desired station due to the lack of parking slots, or when the user is highly influenceable. Differently to other works, instead of employing a single criteria to recommend alternative stations, the proposed system can incorporate a variety of criteria. This result is achieved by providing a defeasible logic-based persuasion engine that is capable of aggregating the results from multiple recommendation rules. The proposed framework is showcased with an example scenario of a bike sharing system.

Measuring customers benefits of click and collect

PurposeClick and collect (or grocery pickup) represents a growing part of the channel strategy of traditional off-line retailers. The aim of this study is to understand how customers develop their perceptions toward this new channel. In other words, what are the key factors explaining the long-term value creation for each “click and collect” system depending on consumers’ profiles?Design/methodology/approachOn the basis of a quantitative survey of 479 respondents, this research uses confirmatory analyses based on the partial least square path modeling.FindingsBased on the structural model, the study finds that the customers’ relations, website and pickup station are the most important factors creating value for customers whatever the internet grocery shopping model. The global conceptual model has been implemented under many variations to test the age effect and the kind of click and collect model. It is made evident that customers’ benefits vary regarding the kind of click and collect model and the age of customers.Research limitations/implicationsThis research allows a better understanding of the performance of the click and collect system by looking at the key factors that maximize the customers’ value and those that decrease it. Results precisely show variations of those factors according to the customer’s profile and the click and collect model.Originality/valueThis quantitative paper studies customer behaviors toward their usual retailer and their relationship with them. To do so, segmented approaches of the causal model are retained to provide specific recommendations.

Sarcoidosis in an Italian province. Prevalence and environmental risk factors.

Background and aimSarcoidosis is a systemic granulomatous inflammatory disease whose causes are still unknown and for which epidemiological data are often discordant. The aim of our study is to investigate prevalence and spatial distribution of cases, and identify environmental exposures associated with sarcoidosis in an Italian province.MethodsAfter georeferentiation of cases, the area under study was subdivided with respect to Municipality and Health Districts and to the altitude in order to identify zonal differences in prevalence. The bioaccumulation levels of 12 metals in lichen tissues were analyzed, in order to determine sources of air pollution. Finally, the analysis of the correlation between metals and between pickup stations was performed.Results223 patients were identified (58.3% female and 41.7% male of total) and the mean age was 50.6±15.4 years (53.5±15.5 years for the females and 46.5±14.4 for the males). The mean prevalence was 49 per 100.000 individuals. However, we observed very heterogeneous prevalence in the area under study. The correlations among metals revealed different deposition patterns in lowland area respect to hilly and mountain areas.ConclusionsThe study highlights a high prevalence of sarcoidosis cases, characterized by a very inhomogeneous and patchy distribution with phenomena of local aggregation. Moreover, the bioaccumulation analysis was an effective method to identify the mineral particles that mostly contribute to air pollution in the different areas, but it was not sufficient to establish a clear correlation between the onset of sarcoidosis and environmental risk factors.

Notes on the single route lateral transhipment problem

Previous research has analyzed deterministic and stochastic models of lateral transhipments between different retailers in a supply chain. In these models the analysis assumes given fixed transhipment costs and determines under which situations (magnitudes of excess supply and demand at various retailers) the transhipment is profitable. However, in reality, these depend on aspects like the distance between retailers or the transportation mode chosen. In many situations, combining the transhipments may save transportation costs. For instance, one or more vehicle routes may be used to redistribute the inventory of the potential pickup and delivery stations. This can be done in any sequence as long as the vehicle capacity is not violated and there is enough load on the vehicle to satisfy demand. The corresponding problem is an extension of the one-commodity pickup and delivery traveling salesman and the pickup and delivery vehicle routing problem. When ignoring the routing aspect and assuming given fixed costs, transhipment is only profitable if the quantities are higher than a certain threshold. In contrast to that, the selection of visited retailers is dependent on the transportation costs of the tour and therefore the selected retailers are interrelated. Hence the problem also has aspects of a (team) orienteering problem. The main contribution is the discussion of the tour planning aspects for lateral transhipments which may be valuable for in-house planning but also for price negotiations with external contractors. A mixed integer linear program for the single route and single commodity version is presented and an improved LNS framework to heuristically solve the problem is introduced. Furthermore, the effect of very small load capacity on the structure of optimal solutions is discussed.

Simulation and Analysis of Noise Control Scheme for Hangzhou Cigarette Factory New Packing Workshop

Based on the noise test data of existing workshop, the noise of new packing workshop was studied. The effection of several noise control scheme was predicted by simulation and analysis method, and the control scheme five was chose finally ,by which average noise reduction was about 4.5dB,and 8h equivalent continuous A-weighted sound pressure level of the pick-up coil station and packaging machine station was 84.9dB and 83.2dB respectively, the working environment of the new workshop was effectively improved, and the investment was estimated.

A hybrid hub-and-spoke postal logistics network with realistic restrictions: A case study of Korea Post

Postal logistics has a complex transportation network for efficient mail delivery. Therefore, a postal logistics network consists of various functional sites with a hybrid hub-and-spoke structure. More specifically, there are multiple Delivery & Pickup Stations (D&PSs), multiple Mail Processing Centers (MPCs), and one Exchange Center (EC). In this paper, we develop two mathematical models with realistic restrictions for Korea Post for the current postal logistics network by simultaneously considering locations and allocations. We propose an Integer Linear Programming (ILP) model for transportation network organization and vehicle operation and a Mixed Integer Linear Programming (MILP) model that considers potential ECs for decision making while simultaneously regarding the EC location, transportation network organization, and vehicle operation. We use modified real data from Korea Post. Additionally, we consider several scenarios for supporting EC decision makers. The proposed models and scenarios are very useful in decision making for postal logistics network designers and operators.

An integrated approach for the cell formation and layout design in cellular manufacturing systems

In this paper, a comprehensive model is presented for cell formation and layout design in cellular manufacturing systems (CMS). The proposed model incorporates an extensive coverage of important operational features and especially layout design aspects to determine optimal cell configuration and Intra and Inter-cell layout in CMS. Hence, proposed integrated approach attempts to design intra and inter-cell layout and material handling flow path structure simultaneously. We examine the great potential benefits of providing these features consist of routing flexibility, operation sequence, machine capacity, considering number of cells as a decision variable, un-equal dimension of machines, free machines and cells orientation, and considering pickup and drop off station for each cell. In order to show the effects and important of integrated design in the CMS, two approaches, sequentially and integrated, have been investigated and demonstrate the integrated approach improve the quality of obtained solution. The proposed model is a mixed integer non-linear programme. Linearisation procedures are proposed to transfer it into a linearised mixed integer programming formulation. Computational results are presented with the linearised formulation. We presented several enhancements in terms of valid inequalities and extensions to the proposed model in order to improve its computational performance. Finally, concluding remarks are provided.

An integrated approach to determine the block layout, AGV flow path and the location of pick-up/delivery points in single-loop systems

Layout design and material handling system design are two of the major aspects of facility planning. Although both aspects directly influence each other, the classical approach to the layout design is carried out in two separate steps: in the first step the block layout, i.e. the location of the departments in the workshop, is constructed, and in the second step, the material handling system is designed. The separate optimisation of these two aspects of the problem leads to solutions that can be far from the global optimum. In this paper, we develop an integrated algorithm to design the facilities and material handling systems. We focus on single-loop AGV systems. The proposed algorithm determines the block layout, AGV single-loop flow path and pick-up delivery stations, simultaneously. The associated from–to chart and the area of departments are the principal inputs of the algorithm. The objective is minimising total material flow distance among all departments. The results of our computational experiments show the algorithm was coded using MATLAB 7.0, and that our integrated algorithm is more efficient in terms of both the objective function value and the runtime.