47 research outputs found
A hybrid metaheuristic for the time-dependent vehicle routing problem with hard time windows
This article paper presents a hybrid metaheuristic algorithm to solve the time-dependent vehicle routing problem with hard time windows. Time-dependent travel times are influenced by different congestion levels experienced throughout the day. Vehicle scheduling without consideration of congestion might lead to underestimation of travel times and consequently missed deliveries. The algorithm presented in this paper makes use of Large Neighbourhood Search approaches and Variable Neighbourhood Search techniques to guide the search. A first stage is specifically designed to reduce the number of vehicles required in a search space by the reduction of penalties generated by time-window violations with Large Neighbourhood Search procedures. A second stage minimises the travel distance and travel time in an ‘always feasible’search space. Comparison of results with available test instances shows that the proposed algorithm is capable of obtaining a reduction in the number of vehicles (4.15%), travel distance (10.88%) and travel time (12.00%) compared to previous implementations in reasonable tim
Tourism and the smartphone app: capabilities, emerging practice and scope in the travel domain.
Based on its advanced computing capabilities and ubiquity, the smartphone has rapidly been adopted as a tourism travel tool.With a growing number of users and a wide varietyof applications emerging, the smartphone is fundamentally altering our current use and understanding of the transport network and tourism travel. Based on a review of smartphone apps, this article evaluates the current functionalities used in the domestic tourism travel domain and highlights where the next major developments lie. Then, at a more conceptual level, the article analyses how the smartphone mediates tourism travel and the role it might play in more collaborative and dynamic travel decisions to facilitate sustainable travel. Some emerging research challenges are discussed
Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.
BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700
A drone service to support the Isle of Wight NHS in the UK
With interest in drone delivery growing throughout the world, this study explores the challenges associated with developing a medical drone logistics service to support the National Health Service on the Isle of Wight in the UK. Two separate trials were undertaken to investigate the potential for drone delivery in this area, carrying medical goods and aseptic cancer medicines. The first trial took place using a fixed-wing drone during COVID-19 lockdown restrictions, whilst the second used hybrid fixed-wing vertical take-off and landing (VTOL) drone. Key findings suggested that electric VTOL drones present significant advantages in terms of point-to-point direct servicing, emissions, and time-savings, though range and payload limitations introduce further challenges. Legislation, airspace management, and technology findings were also made, with legacy regulations causing barriers to carriage of medical goods by drone. Future work seeks to understand the costs and benefits of a more sustained service in a medical setting
Understanding the challenges of drone medical logistics services in developed nations
Uncrewed Aerial Vehicles (UAVs, or drones) have attracted considerable interest as a potential alternative logistics mode, with many studies suggesting that drones will offer faster and more reliable goods transport, whilst reducing associated energy, emissions, and costs compared to traditional modes. This may be true in some select settings and industries, but there are many barriers to achieving widespread implementation, particularly in developed nations.The number of trials of drone delivery has increased in recent years, with the majority being proof-of-concept experiments, never achieving sustained commercial operation. Furthermore, several major players in the logistics industry, e.g., Amazon and DHL, have more recently scaled back their development of such technologies, suggesting there are greater challenges that make the integration of UAVs into existing logistics operations less viable. Arguably the most successful drone delivery system in the world is primarily based in Rwanda, where Zipline routinely deliver blood stocks from central hubs, reaching hospitals significantly faster and more reliably than by road. To the authors’ knowledge, Zipline remains the only commercial national drone logistics operation currently active in the world, posing the question as to why take-up has not been more rapid.There is a general trend towards using drones in the medical sector, where there is potential for expedited delivery of time-sensitive, high-value cargoes to have significant impacts on patient care. Evidence identifies a range of trials carrying goods, such as diagnostic specimens, vaccines, and blood stocks, where delivery times are critical to ensure goods are outside of controlled conditions for as little time as possible or to improve the health outcomes of patients. Whilst this may give some perceived benefits, current legislation with regards to good carriage has not been designed for or applied to autonomous, uncrewed aircraft. In the case of UAVs, their vibration profiles can be significantly different to that of traditional land-based modes, with higher frequencies potentially damaging some of the more sensitive medical products (e.g., haemolysis of blood, etc.). As a result, UAV operators will need to evidence that their platforms do not adversely affect the products carried.To a certain extent, packaging may assist in this endeavour; however, regulations and industry standards may also limit the scope to adapt designs and hence limit the opportunities for UAVs. Dangerous goods regulations prescribe specific design criteria to reduce the likelihood of spillage and damage, and medical regulators require that temperature ranges are not exceeded during transit. This has led to rigorously tested standardised packaging being widely adopted in developed nations, leaving little margin for change which impacts on the minimum carrying requirements for UAVs. Furthermore, until UAVs are more widely adopted, these standards are unlikely to change, meaning that in the short term, drone platforms need to be selected such that the weights and volumes of existing payloads can be carried.Additional safety precautions in developed nations limit the use of package drop systems, meaning vertical take-off and landing (VTOL) functionality will be required to realise the benefits of point-to-point delivery. Meanwhile, a fixed-wing element will enable a greater travel range, particularly if electrically powered. Thus, for anything meaningful to be carried, it is likely that the UAVs used will be fairly large, and VTOL-fixed-wing hybrid setups. In the authors’ experience of testing such technology, a 5-metre wingspan drone with 0.75-metre propellors meets these requirements. Despite meeting the payload requirements, the selected drone does introduce some further limitations with regards to the availability of practical landing sites which don’t detract from their existing function (e.g., removal of public greenspace). The addition of overflight risk also restricts the scope for straight-line flights in order to reduce safety concerns in the event of a crash.Amongst further challenges, it may appear that drone services in developed nations are extremely limited in scope; however, there are still some use cases that will benefit from such a service. Factors that limit the potential of surface transportation, such as road quality, detour index/circuity factor (i.e., how indirect routes are), and the payload due to be carried, can all contribute to how great the benefits of a drone service can be. Through a comparison of successful delivery services, this research also explores what it takes to better existing logistics methods
Overview of ‘Internet of Cars’ digital artist contributions
This document serves as an index to the pieces created as part of the ‘Internet of Cars’ digital artist interaction as part of the EU funded 6th Sense Project.<br/
Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles
UK logistics fleets face increasing competitive pressures due to volatile fuel prices and the small profit margins in the industry. By reducing fuel consumption, operational costs and carbon emissions can be reduced. While there are a number of technologies that can reduce fuel consumption, it is often difficult for logistics companies to identify which would be the most beneficial to adopt over the medium and long terms. With a myriad of possible technology combinations, optimising the vehicle specification for specific duty cycles requires a robust decision-making framework. This paper combines simulated truck and delivery routes with a metaheuristic evolutionary algorithm to select the optimal combination of low-carbon technologies that minimise the greenhouse gas emissions of long-haul heavy goods vehicles during their lifetime cost. The framework presented is applicable to other vehicles, including road haulage, waste collection fleets and buses by using tailored parameters in the heuristics model
A hybrid metaheuristic for the time-dependent vehicle routing problem with hard time windows
This article paper presents a hybrid metaheuristic algorithm to solve the time-dependent vehicle routing problem with hard time windows. Time-dependent travel times are influenced by different congestion levels experienced throughout the day. Vehicle scheduling without consideration of congestion might lead to underestimation of travel times and consequently missed deliveries. The algorithm presented in this paper makes use of Large Neighbourhood Search approaches and Variable Neighbourhood Search techniques to guide the search. A first stage is specifically designed to reduce the number of vehicles required in a search space by the reduction of penalties generated by time-window violations with Large Neighbourhood Search procedures. A second stage minimises the travel distance and travel time in an ‘always feasible’search space. Comparison of results with available test instances shows that the proposed algorithm is capable of obtaining a reduction in the number of vehicles (4.15%), travel distance (10.88%) and travel time (12.00%) compared to previous implementations in reasonable tim
Improving the efficiency of patient diagnostic specimen collection with the aid of a multi-modal routing algorithm
The Sustainable Specimen Collection Problem (SSCP), in which diagnostic specimens are collected from GP surgeries (doctor’s office/clinics) and subsequently transported to a hospital laboratory for analysis using more sustainable transport modes, is introduced in this paper. Using a weightedobjective function, we solve a new multi-objective problem using cycle consolidation to limit driving time and the numbers of vans used whilst improving overall service quality, reducing costs and emissions. This particular heterogeneous vehicle routing problem is explored and applied to tworeal-world case studies in the UK, where 97 and 22 sites (respectively) are currently served, using a column generation based heuristic algorithm with some additional improvement heuristics. The results demonstrated a potential improvement in the system’s maximum delivery time between 41% and 74% compared to business-as-usual activity using solely road vehicles. Road vehicle (van) fleets could be reduced by up to 40%, and the total driving time across the fleet by between 41% and 65%. Operational costs were estimated to increase by up to 38%, though additional workloads for gig-economy cycle couriers and improvement in specimen quality and service reliability may make this trade-off worthwhile. Tailpipe CO2 emissions were also reduced by up to 43%. The proposed algorithm was effective, reducing computational time by up to 99% whilst achieving an average of 5% deviation from optimality