Total Delivery Time Research Articles

Optimal Probabilistic Scheduling in Time Slotted Multiple Access

This paper presents an efficient scheduling model for the delivery of sensing data in networks that use time division multiple access. The model is capable of achieving the optimal solution in terms of total delivery time, given certain constraints on radio resources. The proposed solution adopts a probabilistic approach which is based on a problem formulation utilizing chained binomial distributions.

A comprehensive study of vehicle routing problem with time windows using an improved multi-objective evolutionary algorithms

The vehicle routing problem with time windows (VRPTW) which has both capacity and time constraints is an extension of vehicle routing problem (VRP). The problem is solved by optimizing routes for the vehicles so as to meet all given constraints as well as to minimize travelling distance and number of vehicles. This paper proposes to analyze a multi objective evolutionary algorithm (MOEA) that incorporates Various heuristics for local exploitation in the evolutionary search and the concept of pareto’s optimality to solve multi objective optimization in VRPTW. In this paper we model VRPTW as a modified version specialized for a multi objective context, using Evolutionary Algorithm to get a set of pareto optimal solutions considering three objectives, the number of vehicles, the total travel distance and the total delivery time at the same time. This new approach is validated with very good results and the comparison is performed on a standard benchmark problems showing that the algorithm outperforms highly competitive results compared with previously published studies.

Fuzzy bi-objective inventory-routing problem for blood products in a hospital network during disasters: two multi-objective meta-heuristic approaches

Post-disaster inventory-routing problem consisting of a blood products' supplier and a set of hospitals is investigated. With respect to the different scenarios of roads' availability, the goal of the proposed model is to establish a trade-off between the minimisation of total costs and total delivery time of blood products. Due to the criticality of platelets and red blood cells in disasters, only these two perishable items are addressed. The shortage and wastage costs are predicted based on the conformity measures of patient and donator. The demands are considered as a set of fuzzy numbers due to the lack of sufficient precise data. The model is solved exactly using ε-constraint; however, for large-sized problems, two meta-heuristics, i.e., NSGA-II and MOSA are developed. Comparing the results of NSGA-II and MOSA to those of ε-constraint confirms the efficiency of solution algorithms. Moreover, NSGA-II outperforms MOSA regarding the solution quality; but, MOSA needs fewer computational efforts.

The traveling salesman problem with release dates and drone resupply

This paper introduces the Traveling Salesman Problem with Release Dates and Drone Resupply, which consists of finding a minimum time route for a single truck that can receive newly available orders en route via a drone sent from the depot. We assume that each order’s release date is known at the time of delivery planning. This context is common for many applications, notably last-mile logistics. We develop a Mixed-Integer Linear Program and a solution approach for larger instances based on decomposing the problem into the truck-routing and the drone-resupply decisions. Numerical experiments show that using drones for resupply can reduce the total delivery time by up to 20%. Additionally, experiments show that the decomposition can rapidly obtain high-quality solutions. For instances of 10 and 15 customers, the decomposition solved the majority to optimality, with a trivial gap. For larger instances, this approach provided lower delivery times than a traditional parcel delivery system using a truck only. Investigations on the effects of drone speed, drone capacity, depot location, constraint addition, and allowing the truck to return to the depot are studied. We consider instances up to 50 customers.

Research progress on logistics network optimization under low carbon constraints

In this paper, a literature review was conducted on the optimization of logistics network under low carbon constraints. This paper summarized the basic research process of logistics network optimization, and discussed the basic problems of logistics network optimization (distribution center location and vehicle distribution route optimization) and the compound optimization problems of logistics network (forward logistics network optimization and reverse logistics network optimization). In this paper, we mainly discuss the mathematical model constructed by one or more of the goals of minimum carbon emissions, minimum sum of total costs, minimum total delivery time and minimum total delivery distance, and the solving strategies using heuristic algorithms such as particle swarm optimization, genetic algorithm, and ant colony algorithm. It provided the latest technology in this field for the researchers of enterprise logistics network model and points out the future development trend.

Minimal fluoroscopy approach in current clinical practice with a novel ablation technology for supraventricular tachycardia: a large multicenter experience from an Italian registry

Abstract Background Electrophysiological studies and ablation procedures expose both physicians and patients to a large amount of radiation. Most of 3-D mapping systems provide improved tracking of catheters, possibly allowing relevant reductions in radiation exposure. No data exists on the ability of the Rhythmia mapping system to minimize fluoroscopy time and dose. Purpose To report preliminary data on feasibility and safety of a minimal fluoroscopic approach using the Rhythmia mapping system in supraventricular tachycardia (SVT) procedures. Methods Consecutive patients indicated for arrhythmia ablation were enrolled in the CHARISMA study at 12 centers. For our purpose consecutive right-side procedures performed through a minimal fluoroscopy approach with the Rhythmia mapping system were analyzed. A 3D geometry of chambers of interest was reconstructed on the basis of the electroanatomic information taken from the mapping system. Fluoroscopy was used only if deemed necessary. Results This analysis included 266 patients (mean age = 57±17 years, 57% male) undergoing SVT procedures (120 AVNRT, 91 AFL, 32 AP, 11 AT and 12 other right atrial procedures). In all cases, diagnostic EP and ablation catheters were positioned using a low fluoroscopic electroanatomic guided approach. The mean fluoroscopy time needed for each procedure was 55±128 s. The median reconstructed RA volume was 92 [63–131] ml in a median mapping time of 11 [7–17] min. The median number of radiofrequency ablations to terminate each arrhythmia was 6 [3–12] (total RF delivery time of 291 [180–505] s). Sixty-five percent of the procedures (n=174) were completed with less than 10 s of fluoroscopy. Low fluoroscopy approach with less than 10 s (minimal fluoroscopy approach) was most frequently obtained in case of AVNRT (91, 76%) compared to other arrhythmias' ablation (83, 57%, p=0.001) Achievement of a minimal fluoroscopic approach was not affected by operator's experience (65% vs 66%, p=1.00, respectively within physician with more or less of 10 years of active practice), whereas it was affected by presence of a fellow in training during the procedure (72% without fellow vs 26% with fellow, p<0.0001). A 100% rate of acute success was observed, and no procedure-related complications occurred. At multivariate logistic regression analysis adjusted for baseline confounders, both the total number of RF ablations (OR: 0.93 (95% CI:0.88 to 0.96; p=0.0053) and the presence of a fellow in training during the procedure (OR: 0.29; 95% CI: 0.1 to 0.87; p=0.0278) had an inverse association to the achievement of a minimal fluoroscopic approach. Conclusions In our preliminary experience, arrhythmias' ablation through minimal fluoroscopy approach with the use of a novel ablation technology seems to be safe, feasible, and effective in common right atrial arrhythmias. Use of fluoroscopy can be dramatically reduced in most cases, without any reduction of the safety and acute effectiveness profile. Funding Acknowledgement Type of funding source: None

Plan-Delivery-Time-Constrained Inverse Optimization for High-Throughput PBS Proton RT

Proton RT remains a limited resource that can only accommodate small number of cancer patients. Given that most modern proton centers use the multi-room shared-beam layout to parallelize patient setup, the major throughput-limiting factor is plan delivery time (primarily dose delivery time and energy switching time). This project will develop novel plan-delivery-time-constrained inverse optimization algorithms to achieve the significant reduction of plan delivery time for high-throughput pencil beam scanning (PBS) proton RT. The PBS dose rate is linearly proportional to the minimum-monitor-unit (MU) constraint. Thus, the increase of MU threshold can increase dose rate and therefore reduce dose delivery time. However, the room to increase this threshold is very limited with a single fixed MU threshold for all PBS spots as is assumed by current methods, since the plan quality is often significantly deteriorated before reaching any meaningful reduction of dose delivery time. To allow a significant reduction of dose delivery time while ensuring the plan quality, we propose to use variable energy-dependent MU thresholds to relax the tradeoff between dose delivery time and plan quality. On the other hand, although energy switching time is the secondary factor for total plan delivery time, it becomes relatively more important as dose delivery time is significantly reduced. Thus, energy switching time is modeled via group sparsity. New optimization algorithms via iterative convex relaxation are developed to solve these non-convex optimization problems. In addition, our methods can provide the efficiency-quality Pareto surface via multi-criteria optimization regarding the tradeoff between delivery efficiency and plan quality. With variable energy-dependent MU thresholds, our new method achieved 46.7%, 32.6%, and 33.3% reduction of dose delivery time respectively for prostate, lung and brain cases. Compared with plans optimized with a single MU threshold that corresponded to a 26.7% reduction of dose delivery time, our new method significantly improved plan quality in terms of both CTV coverage and OAR sparing. Moreover, the dose delivery time was further reduced to 25.7%, 34.9%, and 41.3% respectively, accepting a slightly degraded plan quality that still met all clinical planning constraints. On the other hand, our group-sparsity-regularized method reduced number of energy layers (or equivalently energy switching time) to 78%, 76%, and 61% respectively for prostate, lung and HN cases, while comparable plan quality was preserved. Moreover, the energy switching time was further reduced to 54%, 57%, and 37% respectively, accepting a slightly degraded plan quality that still met all clinical planning constraints. Novel plan-delivery-time-constrained optimization methods have been developed for high-throughput PBS proton RT.

The multiple flying sidekicks traveling salesman problem with variable drone speeds

This research considers unmanned aerial vehicles (UAVs) that may travel at varying speeds in a last-mile delivery system involving a single truck and a fleet of UAVs. In existing truck-and-UAV delivery models that assume constant or unlimited UAV endurance, the natural conclusion is that operating UAVs at higher speeds will either decrease, or have no adverse effect on, total delivery times. However, in reality, UAV power consumption is a nonlinear function of both speed and parcel weight; flying at high speeds can dramatically reduce flight ranges, thus limiting the effectiveness of these logistics systems. This paper addresses the tradeoffs between speed and range in a new variant of the combined truck/UAV delivery problem in which UAV speeds are treated as decision variables. A three-phased algorithm is provided that dynamically adjusts UAV speeds to achieve superior performance, with the goal of minimizing the total delivery time (or makespan). Results indicate that significant time savings can be achieved by operating UAVs at variable speeds. Furthermore, under certain conditions, optimizing UAV speeds also results in shorter truck travel distances, reduced UAV energy consumption per trip, and less UAV loitering while waiting to rendezvous with the truck.

Fly Slower, Deliver Faster: the Multiple Flying Sidekicks Traveling Salesman Problem with Variable Drone Speeds

This research considers unmanned aerial vehicles (UAVs) that may travel at varying speeds in a last-mile delivery system involving a single truck and a fleet of UAVs. In existing truck-and-UAV delivery models that assume constant or unlimited UAV endurance, the natural conclusion is that operating UAVs at higher speeds will either decrease, or have no adverse effect on, total delivery times. However, in reality, UAV power consumption is a nonlinear function of both speed and parcel weight; flying at high speeds can dramatically reduce flight ranges, thus limiting the effectiveness of these logistics systems. This paper addresses the tradeoffs between speed and range in a new variant of the combined truck/UAV delivery problem in which UAV speeds are treated as decision variables. A three-phased algorithm is provided that dynamically adjusts UAV speeds to achieve superior performance, with the goal of minimizing the total delivery time (or makespan). Results indicate that significant time savings can be achieved by operating UAVs at variable speeds. Furthermore, under certain conditions, optimizing UAV speeds also results in shorter truck travel distances, reduced UAV energy consumption per trip, and less UAV loitering while waiting to rendezvous with the truck.

Technical Note: Plan-delivery-time constrained inverse optimization method with minimum-MU-per-energy-layer (MMPEL) for efficient pencil beam scanning proton therapy.

This work aims to reduce dose delivery time of pencil beam scanning (PBS) proton plans, which is the dominant factor of total plan delivery time. A proton PBS system, such as Varian ProBeam proton therapy system, can be equipped with the proton dose rate that is linearly proportional to the minimum monitor unit (MU) (i.e., number of protons) of PBS spots before saturation. Thus dose delivery time can be potentially reduced by increasing the MU threshold. However, commercially available treatment planning systems and current methods only allow for a single MU threshold globally for all PBS spots (i.e., all energy layers), and consequently the room to increase this minimum-MU for reducing dose delivery time is very limited since higher minimum-MU can greatly degrade treatment plan quality. Two major innovations of this work are the proposal of using variable MU thresholds locally adaptive to each energy layer, that is, minimum-MU-per-energy-layer (MMPEL), for reducing dose delivery time, and the joint optimization of plan delivery time and plan quality. Minimum-MU-per-energy-layer is formulated as a constrained optimization problem with objectives of dose-volume-histogram based planning constraints and plan delivery time, and minimum-MU constraints per energy layer for deliverable PBS spots. Minimum-MU-per-energy-layer is solved by iterative convex relaxations via alternating direction method of multipliers. Representative prostate, lung, brain, head-and-neck, breast, liver and pancreas cases were used to validate MMPEL. Minimum-MU-per-energy-layer reduced dose delivery time to 53%, 67%, 67%, 53%, 54%, 32%, and 14% respectively while maintaining a similar plan quality. Accepting a slightly degraded plan quality that still met all physician planning constraints, the treatment time could be further reduced to 26%, 35%, 41%, 34%, 32%, 16%, and 11% respectively, or in another word MMPEL accelerated the PBS plan delivery by 2-10 fold. A new proton PBS treatment planning method MMPEL with variable energy-adaptive MU thresholds is developed to optimize dose delivery time jointly with plan quality. The preliminary results suggest that MMPEL could substantially reduce dose delivery time.

A New Parcel Delivery System with Drones and a Public Train

In this paper, we propose a new parcel delivery system consisting of a public train and drones. The train, an already existing mobile platform in our neighbourhood, follows its normal predefined route and timetable to transport passengers. In the meanwhile, some parcels to be delivered to some customers and a delivery drone are stored on its roof. The drone can launch from the train, deliver the parcel to a customer, and return to the train. It can also travel with the train and replace its battery on the roof via an automatic battery swap system. As the parcel delivery system cannot manage the movement of the train, the route and the timetable of the train need to be accounted carefully to schedule the deliveries. We formulate an optimization problem to minimize the total delivery time of a given set of parcels, and we propose two algorithms. Though the exact algorithm gives the optimal schedule, its computational complexity is exponential to the number of parcels. To make the proposed system possible to be implemented in practice, a suboptimal algorithm is developed, which is more efficient than the exact algorithm and can achieve close performance with the exact algorithm. Additionally, we propose a simple but effective strategy to deal with the uncertainty associated with the train’s timetable. Moreover, the proposed algorithm for the single drone case is modified to deal with the multiple drone case. The effectiveness of the proposed algorithms is verified via computer simulations and comparison with existing methods. The results show that the presented approach is more cost-efficient than the Truck only scheme and the Truck plus Drone scheme. Moreover, the parcel delivery time can be reduced and the delivery area can be enlarged compared to the scheme using drones only.

P1452Low fluoroscopy approach with a novel ablation technology in right side procedures: a large multicenter experience from the CHARISMA registry

Abstract Funding Acknowledgements NO FUNDING Background Electrophysiological studies and ablation procedures expose both physicians and patients to a significant amount of radiation. Nowadays, most of 3-D mapping systems allow for improved tracking of catheters with possible reduction in radiation exposure. No data exists on the ability to minimize fluoroscopy time and dose while using the Rhythmia mapping system. Purpose To report preliminary data on feasibility and safety of a low fluoroscopic approach using the Rhythmia mapping system in SVT procedures. Methods The CHARISMA study is a non-randomized, multicenter, prospective study in which consecutive patients indicated for arrhythmia were enrolled. For our purpose consecutive right-side procedures performed through a low fluoroscopy approach with the Rhythmia mapping system were analyzed. The mapping system was used to create the 3D geometry of chambers of interest and anatomic reference points and to visualize the catheters from the beginning to the end of the procedure. Fluoroscopy was used only if deemed necessary. Results 204 unselected consecutive cases of SVT from 11 centers were included in the study (mean age = 55 ± 18 years, 53% male, 85 AVNRT, 75 AFL, 28 AP, 9 AT and 7 other right atrial procedures). In all the cases, diagnostic EP and ablation catheters were positioned using only the low fluoroscopic guided mapping approach. During the study, a total of 7157 s of fluoroscopy was needed in 204 patients (51 ± 137 s per procedure). One hundred fourty-one procedures (69%) were completed with less than 10 seconds of fluoroscopy, whereas in 169 (83%) of the cases the fluoroscopy time was lower than 60 seconds. Low fluoroscopy approach with less than 10 seconds was less frequently obtained in case of AFL (46, 61.3%) compared to AVNRT ablation (65, 76.5%, p = 0.041) whereas no differences were found comparing with AP (21, 75%, p = 0.248). The median reconstructed RA volume was 94[65-133] ml in a median mapping time of 11 [6-16] min. The median number of radiofrequency ablations to terminate each arrhythmia was 5 [3-12] (total RF delivery time of 293 [180-505] sec). A 100% rate of acute success was observed in our case series. No complications occurred. Conclusions In our preliminary experience, arrhythmias ablation through low fluoroscopy approach and the use of a novel ablation technology seems to be safe, feasible, and effective in common right atrial arrhythmias. Use of fluoroscopy can be nearly avoided in most cases, without any reduction of the safety and effectiveness profile.

DAPF: Delay‐aware packet forwarding for driving safety and efficiency in vehicular networks

This study proposes an effective delay-aware packet forwarding (DAPF) for driving safety and efficiency in vehicular networks. Vehicular ad hoc networks have been an emerging technology for vehicular communication for the last few decades, but still, it has many challenging issues such as on-time dissemination of message at an emergency situation (e.g. accident and obstacle) to the vehicles having the same route to their destinations. This on-time dissemination can prevent further collision of vehicles and road traffic congestion. In this study, the authors propose an effective way of selecting the processing position of a message among a cluster head, road-side unit (RSU), and vehicular cloud, on the basis of total delivery time and cost. They further show that this effective selection and on-time dissemination helps the upcoming vehicles to select an appropriate route to their destinations. Through simulation results, it is shown that their DAPF outperforms other schemes in terms of packet delivery time.

A novel energy layer optimization framework for spot-scanning proton arc therapy.

Spot-scanning proton arc therapy (SPAT) is an emerging modality to improve plan conformality and delivery efficiency. A greedy and heuristic method is proposed in the existing SPAT algorithm to select energy layers and sequence energy switching with gantry rotation, which does not promise optimality in either dosimetry or efficiency. We aim to develop a method to solve the energy layer switching and dosimetry optimization problems in an integrated framework for SPAT. In an integrated approach, energy layer optimization for spot-scanning proton arc therapy (ELO-SPAT) is formulated with a dose fidelity term, a group sparsity regularization, a log barrier regularization, and an energy sequencing (ES) penalty. The combination of L2,1/2-norm group sparsity regularization and log barrier function allows one energy layer being selected per control point. The ES regularization term sorts the delivery sequence from high energy to low energy to reduce the total energy layer switching time (ELST) and subsequently the total delivery time. Within the ES penalty, the gradient of layer weights between adjacent beams is first calculated along beam direction and then along energy direction. The gradients indicate energy switch patterns between two adjacent beams. The time-wise costly energy switch-up is more heavily penalized in the ES term. This ELO-SPAT method was tested on one frontal base-of-skull (BOS) patient, one chordoma (CHDM) patient with a simultaneous integrated boost, one bilateral head-and-neck (H&N) patient, and one lung (LNG) patient. We compared ELO-SPAT with intensity-modulated proton therapy (IMPT) using discrete beams and SPArc by Ding et al. For the two arc algorithms, both the plans with and without energy sequencing were created and compared. Energy layer optimization for spot-scanning proton arc therapy reduced the runtime of optimization by 84% on average compared with the greedy SPArc method. In both the ELO-SPAT plans with and without ES, one energy layer per control point was selected. Without ES regularization, the energy sequence was arbitrary, with around 40-60 switch-up for the tested cases. After adding ES regularization, the number of energy switch-up was reduced to less than 20. Compared with the energy sequenced SPArc plans, the ELO-SPAT plans with ES led to 24% less total ELST for synchrotron plans and 14% less for cyclotron plans. Both the ELO-SPAT and SPArc plans achieved better sparing compared with the IMPT plans for most Organs-at-risks (OARs), with or without ES. Without ES, the ELO-SPAT plans achieved further improvement of the OARs compared with the SPArc plans, with an averaged reduction of OAR [Dmean, Dmax] by [1.57, 3.34] GyRBE. Adding the ES regularization degraded the plan quality, but the ELO-SPAT plans still had comparable or slightly better sparing than the SPArc plans with ES, with an averaged reduction of OAR [Dmean, Dmax] by [1.42, 2.34] GyRBE. We developed a computationally efficient spot-scanning proton arc optimization method, which solved energy layer selection and sequencing in an integrated framework, generating plans with good dosimetry and high delivery efficiency.

OPTIMASI PENDISTRIBUSIAN PRODUK MENGGUNAKAN MODEL FUZZY MULTIOBJEKTIF CYCLICAL INVENTORY ROUTING PROBLEM

In distribution activities, travel time is influenced by several factors, such as vehicle conditions, traffic conditions and road conditions. Uncertain traffic conditions cause the travel time can not be defined with certainty (uncertain). If several variables are in a uncertain condition then a deterministic approach is not appropriate. Fuzzy approach, can be used to overcome uncertainty conditions. In this study, the optimal route for chicken egg delivery using the fuzzy Multiobjective Cyclical Inventory Routing Problem (FMOCIRP) model with time and cost is expressed by triangular fuzzy numbers. Model completion using Winqsb software. An optimal shipping route is obtained with a total cost of Rp 114,000 and a total delivery time of 132 minutes. The first optimal delivery route is distributor, retailer 1, retailer 2, retailer 3 and back to the distributor. The second route is distributor, retailer 5, retailer 4 and back to the distributor.

Improve the dosimetric outcome in bilateral head and neck cancer (HNC) treatment using spot-scanning proton arc (SPArc) therapy: a feasibility study

BackgroundTo explore the dosimetric improvement, delivery efficiency, and plan robustness for bilateral head and neck cancer (HNC) treatment utilizing a novel proton therapy technique – the spot-scanning proton arc (SPArc) therapy.MethodsWe evaluated fourteen bilateral HNC patients retrospectively. Both SPArc and 3-field Intensity Modulated Proton Therapy (IMPT) plans were generated for each patient using the same robust optimization parameters. The prescription doses were 70Gy (relative biological effectiveness (RBE) for CTV_high and 60Gy[RBE] for CTV_low. Clinically significant dosimetric parameters were extracted and compared. Root-mean-square deviation dose (RMSDs) Volume Histogram(RVH) was used to evaluate the plan robustness. Total treatment delivery time was estimated based on the machine parameters.ResultsThe SPArc plan was able to provide equivalent or better robust target coverage while showed significant dosimetric improvements over IMPT in most of the organs at risk (OARs). More specifically, it reduced the mean dose of the ipsilateral parotid, contralateral parotid, and oral cavity by 25.8%(p = 0.001), 20.8%(p = 0.001) and 20.3%(p = 0.001) respectively compared to IMPT. This technique reduced D1 (the maximum dose covering 1% volume of a structure) of cord and brain stem by 20.8% (p = 0.009) and 10.7% (p = 0.048), respectively. SPArc also reduced the average integral dose by 17.2%(p = 0.001) and external V3Gy (the volume received 3Gy[RBE]) by 8.3%(p = 0.008) as well. RVH analysis showed that the SPArc plans reduced the dose uncertainties in most OARs compared to IMPT, such as cord: 1.1 ± 0.4Gy[RBE] vs 0.7 ± 0.3Gy[RBE](p = 0.001), brain stem: 0.9 ± 0.7Gy[RBE] vs 0.7 ± 0.7Gy[RBE](p = 0.019), contralateral parotid: 2.5 ± 0.5Gy[RBE] vs 2.2 ± 0.6Gy[RBE](p = 0.022) and ipsilateral parotid: 3.1 ± 0.7Gy[RBE] vs 2.8 ± 0.6Gy[RBE](p = 0.004) respectively. The average total estimated treatment delivery time were 283.4 ± 56.2 s, 469.2 ± 62.0 s and 1294.9 ± 106.7 s based on energy-layer-switching-time (ELST) of 0.1 s, 1 s, and 5 s respectively for SPArc plans, compared to the respective values of 328.0 ± 47.6 s(p = 0.002), 434.1 ± 52.0 s(p = 0.002), and 901.7 ± 74.8 s(p = 0.001) for 3-field IMPT plans. The potential clinical benefit of utilizing SPArc will lead to a decrease in the mean probability of salivary flow dysfunction by 31.3%(p = 0.001) compared with IMPT.ConclusionsSPArc could significantly spare OARs while providing a similar or better robust target coverage compared with IMPT in the treatment of bilateral HNC. In the modern proton system with ELST less than 0.5 s, SPArc could potentially be implemented in the routine clinic with a practical, achievable treatment delivery efficiency.

Comprehensive optimization of the synchronous delivery network in the model of OTMD for traveling salesman problem with drone

Synchronous delivery with different vehicles, as an emerging concept of the delivery network, improves the efficiency of the modern logistics system significantly, which gradually gives birth to a new issue: the traveling salesman problem with drone (TSP-D). In this paper, we propose a one-truck-multiple-drone (OTMD) model on the base of the TSP-D. Compared with the traditional one-truck-one-drone (OTOD) and multiple drones models, our scheme introduces a united objective function into the optimization calculation. In terms of the proposed multiple levels iterative theory, we can compute the optimal synchronous delivery network that takes both the total delivery time and the number of drones into consideration. Four types of customer distributions are employed to investigate the OTMD model and its associated calculation approaches. Comparing the parameters of the optimal network in different delivery models, we study the relationship among the total delivery time, customer distribution and the number of serving drones. These simulation results verify the feasibility and practicality of the OTMD, and demonstrate the features of optimization calculation with different customer distributions, being beneficial to improve the efficiency of the model logistics system.

Paroxysmal atrial fibrillation recurrence after redo procedure-ablation modality impact.

Atrial fibrillation recurrence (AFR) is common after pulmonary vein isolation (PVI), and the rate does not differ between radiofrequency (RF) and cryoballoon (CB) ablation. The aim of this study was to assess the impact of the ablation modality used at the index PVI on the outcome after redo PVI in patients with paroxysmal AF. In this prospective, single-center, non-randomized study, consecutive patients with paroxysmal AF who have undergone the index PVI with either RF ablation (RF group) or 2nd-generation CB (CB group) were included. The primary endpoint was freedom from recurrence of atrial arrhythmia lasting > 30s. A total of 105 patients undergoing redo PVI for paroxysmal AF were included (median age 61years; 24% female; left ventricular ejection fraction (LVEF) 57 ± 8%; left atrial volume index (LAVI) 34 ± 11mm). Index PVI was done either with focal RF (n = 81) or with CB (n = 24) and redo PVI only with focal RF. Total procedure time (139 vs. 113min, p = 0.10) and RF delivery time (1017 vs. 870s, p = 0.33) of the redo PVI were not significantly different. After a median follow-up of 371 (185-470) days, there were no differences between the RF and CB groups regarding the AFR rate after the second PVI (24 vs. 23%, p = 0.89). The Kaplan-Meier analysis showed no difference between the groups regarding AFR freedom time (p = 0.81). In multivariable logistic regression, only coronary artery disease was identified as an independent long-term predictor of AFR (OR 4.15, 95% CI 1.17-14.71, p = 0.027). The ablation modality used at the index PVI has no impact on long-term outcome after redo PVI in patients with paroxysmal AF.

A Performance Comparison of Manual Dispensing and Automated Drug Delivery

Recently, the automatic distribution in pharmacies has solved the problems associated with traditional drug distribution, such as, quality of service to the customers, slow operation speed, inventory management, and savings in labour costs. The main contribution of this article is to present and to highlight the benefits of using a free-fall flow-rack automated storage and retrieval system for automating drug distribution in the pharmacies. For this, a comparison study has been carried out between the automatic and manual drug distribution according to the total delivery time of customer request. The total delivery time of customer request for the automatic distribution was calculated via simulation, while manual distribution was evaluated by an empirical study. 10 scenarios for each customer request have been performed to emulate the real distribution in pharmacies. We found that the deviation between the manual and automatic distribution can reach 94%.

Motivational Interviewing to Encourage Quit Attempts Among Smokers Not Ready to Quit: A Trial-Based Economic Analysis.

This study used data from a randomized controlled trial evaluating the efficacy of motivational interviewing (MI) relative to health education (HE) and brief advice (BA) to encourage quit attempts and cessation in order to determine their relative cost-effectiveness. Urban community residents (n = 255) with low desire to quit smoking were randomized to MI, HE, or BA which differed in communication style and/or number of treatment sessions. Incremental cost-effectiveness ratios were used to compare the intensive interventions (MI and HE) to BA for facilitating quit attempts and smoking cessation. Costs were calculated from the perspective of an agency that might engage in program delivery. Sensitivity analysis examined different assumptions for MI training and pharmacotherapy costs. Total intervention delivery time costs per participant for MI, HE, and BA were $46.63, $42.87, and $2.4, respectively. Cost-effectiveness ratios per quit attempt at 24 weeks were $380 for MI, $272 for HE, and $209 for BA. The cost per additional quit attempt for MI and HE relative to BA was $508 and $301, respectively. The cost per additional quit for MI and HE relative to BA was $2030 and $752, respectively. Four separate sensitivity analyses conducted in our study did not change the conclusion the HE had a lower Incremental Cost-Effectiveness Ratio for both quit attempts and cessation. HE was the most cost-effective of the three types of smoking cessation induction therapies and therefore may be preferable for smokers who are less motivated to quit. Providing valuable cost information in choosing different clinical methods for motivating smokers to quit. All direct costs and activity-based time costs associated with delivering the intervention were analyzed from the perspective of an agency that may wish to replicate these strategies. A randomized controlled trial evaluating the efficacy of MI relative to HE and BA to encourage quit attempts and cessation determined their relative cost-effectiveness. HE was the most cost-effective of the three types of smoking cessation induction therapies and therefore may be preferable. Despite guideline recommendations, MI may not be the best approach to encourage quit attempts in diverse populations. Rather, a structured, intensive HE intervention might be the most cost-effective alternative.