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1

Desaulniers, Guy, and Daniel Villeneuve. "The Shortest Path Problem with Time Windows and Linear Waiting Costs." Transportation Science 34, no. 3 (August 2000): 312–19. http://dx.doi.org/10.1287/trsc.34.3.312.12298.

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2

Wang, Donghai, Menghao Xi, and Yingzhen Chen. "A Dynamic Shelter Location and Victim Resettlement Model Considering Equitable Waiting Costs." International Journal of Environmental Research and Public Health 17, no. 2 (January 10, 2020): 471. http://dx.doi.org/10.3390/ijerph17020471.

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Catastrophic natural disasters cause devastating damage and leave a huge number of homeless people. Waiting for resettlement in a post-disaster environment brings human suffering, which is defined by waiting cost in this paper. Taking into account waiting cost and fairness consideration simultaneously, a mixed integer linear programming model is constructed for the multiperiod location-allocation process. Two fairness indicators are incorporated to guarantee both the whole-process equity and the periodic equity. The model is implemented in the General Algebraic Modeling System (GAMS) and solved by the CPLEX solver. An illustrative example is provided to explain the model characteristics. Furthermore, a case study of the Yushu earthquake is conducted to demonstrate the applicability of the model to practical problems.
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RODRÍGUEZ, Santiago, Fabio Da MOTTA, Giacomo BALBINOTO NETO, and Ajacio BRANDÃO. "EVALUATION AND SELECTION OF CANDIDATES FOR LIVER TRANSPLANTATION: AN ECONOMIC PERSPECTIVE." Arquivos de Gastroenterologia 57, no. 1 (February 2020): 31–38. http://dx.doi.org/10.1590/s0004-2803.202000000-07.

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ABSTRACT BACKGROUND: Over the next 20 years, the number of patients on the waiting list for liver transplantation (LTx) is expected to increase by 23%, while pre-LTx costs should raise by 83%. OBJECTIVE: To evaluate direct medical costs of the pre-LTx period from the perspective of a tertiary care center. METHODS: The study included 104 adult patients wait-listed for deceased donor LTx between October 2012 and May 2016 whose treatment was fully provided at the study transplant center. Clinical and economic data were obtained from electronic medical records and from a hospital management software. Outcomes of interest and costs of patients on the waiting list were compared through the Kruskal-Wallis test. A generalized linear model with logit link function was used for multivariate analysis. P-values <0.05 were considered statistically significant. RESULTS: The costs of patients who underwent LTx ($8,879.83; 95% CI 6,735.24-11,707.27; P<0.001) or who died while waiting ($6,464.73; 95% CI 3,845.75-10,867.28; P=0.04) were higher than those of patients who were excluded from the list for any reason except death ($4,647.78; 95% CI 2,469.35-8,748.04; P=0.254) or those who remained on the waiting list at the end of follow-up. CONCLUSION: Although protocols of inclusion on the waiting list vary among transplant centers, similar approaches exist and common problems should be addressed. The results of this study may help centers with similar socioeconomic realities adjust their transplant policies.
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Yu, Kai, and Jingcheng Yang. "MILP Model and a Rolling Horizon Algorithm for Crane Scheduling in a Hybrid Storage Container Terminal." Mathematical Problems in Engineering 2019 (January 8, 2019): 1–16. http://dx.doi.org/10.1155/2019/4739376.

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This paper investigates the yard crane scheduling problem of a hybrid storage container terminal whose import containers and export containers are stored together in each block. The combination of containers improves the space utilization of a container terminal while it also creates new challenges for the yard crane scheduling. To formulate this problem, we propose a mixed integer linear programming (MILP) model, which jointly optimizes trucks’ waiting costs and penalty costs caused by exceeding waiting time thresholds. Considering the NP-completeness of this scheduling problem, we develop an efficient rolling horizon algorithm based on some heuristics to reduce the computation time. Finally, computational studies are carried out to evaluate the performance of our method and the solutions obtained by CPLEX solver are used for benchmarking purposes.
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Argon, Nilay Tanik, Li Ding, Kevin D. Glazebrook, and Serhan Ziya. "DYNAMIC ROUTING OF CUSTOMERS WITH GENERAL DELAY COSTS IN A MULTISERVER QUEUING SYSTEM." Probability in the Engineering and Informational Sciences 23, no. 2 (February 16, 2009): 175–203. http://dx.doi.org/10.1017/s0269964809000138.

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We consider a network of parallel service stations each modeled as a single-server queue. Each station serves its own dedicated customers as well as generic customers who are routed from a central controller. We suppose that the cost incurred by a customer is an increasing function of her time spent in the system. In a significant advance on most previous work, we do not require waiting costs to be convex, still less linear. With the objective of minimizing the long-run average waiting cost, we develop two heuristic routing policies, one of which is based on dynamic programming policy improvement and the other on Lagrangian relaxation. In developing the latter policy, we show that each station is “indexable” under mild conditions for customers’ waiting costs and also prove some structural results on the admission control problem that naturally arises as a result of the Lagrangian relaxation. We then test the performance of our heuristics in an extensive numerical study and show that the Lagrangian heuristic demonstrates a strong level of performance in a range of traffic conditions. In particular, it clearly outperforms both a greedy heuristic, which is a standard proposal in complex routing problems, and a recent proposal from the heavy traffic literature.
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Haviv, Moshe, and Jan van der Wal. "Equilibrium Strategies for Processor Sharing and Random Queues with Relative Priorities." Probability in the Engineering and Informational Sciences 11, no. 4 (October 1997): 403–12. http://dx.doi.org/10.1017/s0269964800004940.

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We consider a memoryless single-server queue in which users can purchase relative priority so as to reduce their expected waiting costs, which are linear with time. Relative priority is given in proportion to a price paid by customers present in the system. For two service disciplines, (weighted) processor sharing and (weighted) random entrance, we find the unique pure and symmetric Nash equilibrium price paid by the customers.
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7

Adan, I. J. B. F., V. G. Kulkarni, N. Lee, and E. Lefeber. "Optimal routeing in two-queue polling systems." Journal of Applied Probability 55, no. 3 (September 2018): 944–67. http://dx.doi.org/10.1017/jpr.2018.59.

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Abstract We consider a polling system with two queues, exhaustive service, no switchover times, and exponential service times with rate µ in each queue. The waiting cost depends on the position of the queue relative to the server: it costs a customer c per time unit to wait in the busy queue (where the server is) and d per time unit in the idle queue (where there is no server). Customers arrive according to a Poisson process with rate λ. We study the control problem of how arrivals should be routed to the two queues in order to minimize the expected waiting costs and characterize individually and socially optimal routeing policies under three scenarios of available information at decision epochs: no, partial, and complete information. In the complete information case, we develop a new iterative algorithm to determine individually optimal policies (which are symmetric Nash equilibria), and show that such policies can be described by a switching curve. We use Markov decision processes to compute the socially optimal policies. We observe numerically that the socially optimal policy is well approximated by a linear switching curve. We prove that the control policy described by this linear switching curve is indeed optimal for the fluid version of the two-queue polling system.
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Shi, Xiaowei, Zhiwei Chen, Mingyang Pei, and Xiaopeng Li. "Variable-Capacity Operations with Modular Transits for Shared-Use Corridors." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 9 (July 30, 2020): 230–44. http://dx.doi.org/10.1177/0361198120928077.

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Since passenger demand in urban transit systems is asymmetrically distributed across different periods in a day and different geographic locations across the cities, the tradeoff between vehicle operating costs and service quality has been a persistent problem in transit operational design. The emerging modular vehicle technology offers us a new perspective to solve this problem. Based on this concept, we propose a variable-capacity operation approach with modular transits for shared-use corridors, in which both dispatch headway and vehicle capacity are decision variables. This problem is rigorously formulated as a mixed integer linear programming model that aims to minimize the overall system cost, including passenger waiting time costs and vehicle operating costs. Because the proposed model is linear, the state-of-the-art commercial solvers (e.g., Gurobi) can be used to obtain the optimal solution of the investigated problem. With numerical experiments, we demonstrate the feasibility of the mathematical model, verify the effectiveness of the proposed model in reducing overall system costs in transit systems, as well as the robustness of the proposed model with different parameter settings.
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Afifudin, M. Thezar, and Dian P. Sahar. "MODEL OPTIMISASI UNTUK MASALAH MINIMISASI BIAYA PERJALANAN WISATA TUR-TUNGGAL DI ZONA KEPULAUAN." ALE Proceeding 4 (August 17, 2021): 68–75. http://dx.doi.org/10.30598/ale.4.2021.68-75.

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This study aims to develop an optimization model for solving the insular cost minimization single-tour travel problems. The model was developed using an integer non-linear programming approach by considering the selection of departure and arrival points of an island, selecting accommodation points, selecting transportation mode departure schedules, and selecting travel routes both within islands and between islands. The cost components considered include inter-island travel costs, land travel costs, costs at selective points, and costs waiting for departure. A numerical experiment was conducted on the case of planning a tourist route in Maluku, Indonesia. The departure day scenario is built to find out the exact route and schedule on each day of departure with a minimum total cost. In addition, comparisons were also made to the results obtained in the time minimization model that was introduced earlier. The results showed that the model can adapt through variations of solutions to changes in the given parameters and objectives.
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Rieder, Ulrich, and Jürgen Weishaupt. "Customer Scheduling with Incomplete Information." Probability in the Engineering and Informational Sciences 9, no. 2 (April 1995): 269–84. http://dx.doi.org/10.1017/s0269964800003855.

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A stochastic scheduling model with linear waiting costs and unknown routing probabilities is considered. Using a Bayesian approach and methods of Bayesian dynamic programming, we investigate the finite-horizon stochastic scheduling problem with incomplete information. In particular, we study an equivalent nonstationary bandit model and show the monotonicity of the total expected reward and of the Gittins index. We derive the monotonicity and well-known structural properties of the (greatest) maximizers, the so-called stay-on-a-winnerproperty and the stopping-property. The monotonicity results are based on a special partial ordering on .
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Dou, Xueping, and Qiang Meng. "Feeder Bus Timetable Design and Vehicle Size Setting in Peak Hour Demand Conditions." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 10 (May 18, 2019): 321–32. http://dx.doi.org/10.1177/0361198119846462.

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This study proposes a solution to the feeder bus timetabling problem, in which the terminal departure times and vehicle sizes are simultaneously determined based on the given transfer passengers and their arrival times at a bus terminal. The problem is formulated as a mixed integer non-linear programming (MINLP) model with the objective of minimizing the transfer waiting time of served passengers, the transfer failure cost of non-served passengers, and the operating costs of bus companies. In addition to train passengers who plan to transfer to buses, local passengers who intend to board buses are considered and treated as passengers from virtual trains in the proposed model. Passenger attitudes and behaviors toward the waiting queue caused by bus capacity constraints in peak hour demand conditions are explicitly embedded in the MINLP model. A hybrid artificial bee colony (ABC) algorithm is developed to solve the MINLP model. Various experiments are set up to account for the performance of the proposed model and solution algorithm.
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12

Yang, Laurence Tianruo. "THE IMPROVED PARALLEL ICGS METHOD FOR LARGE AND SPARSE UNSYMMETRIC LINEAR SYSTEMS." Parallel Processing Letters 15, no. 04 (December 2005): 459–67. http://dx.doi.org/10.1142/s0129626405002374.

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For the solutions of large and sparse linear systems of equations with unsymmetric coefficient matrices, we propose an improved version of the Conjugate Gradient Squared method (ICGS) method. The algorithm is derived such that all inner products, matrix-vector multiplications and vector updates of a single iteration step are independent and communication time required for inner product can be overlapped efficiently with computation time of vector updates. Therefore, the cost of global communication on parallel distributed memory computers can be significantly reduced. The resulting ICGS algorithm maintains the favorable properties of the algorithm while not increasing computational costs. Data distribution suitable for both irregularly and regularly structured matrices based on the analysis of the non-zero matrix elements is also presented. Communication scheme is supported by overlapping execution of computation and communication to reduce waiting times. The efficiency of this method is demonstrated by numerical experimental results carried out on a parallel distributed memory system.
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13

Rece, Laurentiu, Sorin Vlase, Daniel Ciuiu, Giorgian Neculoiu, Stefan Mocanu, and Arina Modrea. "Queueing Theory-Based Mathematical Models Applied to Enterprise Organization and Industrial Production Optimization." Mathematics 10, no. 14 (July 20, 2022): 2520. http://dx.doi.org/10.3390/math10142520.

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In the paper, a new method was presented using queueing theory models in order to ensure an optimal production department size, optimized production costs and optimal provision. Queueing/waiting mathematical models represent the development matrix for an experimental algorithm and implicitly numerical approach, both successfully applied (and confirmed in practice) in a production section design for a real industrial engineering unit with discussed method technological flow and equipment schemes compatibility. The total costs for a queueing system with S servers depend on the number of servers. The problem of minimizing cost in terms of S was the main aim of the paper. In order to solve it, we estimated all the variables of the system that influence the cost using the Monte Carlo method. For a Jackson queueing network, the involved linear system has good properties such that it can be solved by iterative methods such as Jacobi and Gauss–Seidel.
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14

Aboolian, Robert, Oded Berman, and Majid Karimi. "Probabilistic Set Covering Location Problem in Congested Networks." Transportation Science 56, no. 2 (March 2022): 528–42. http://dx.doi.org/10.1287/trsc.2021.1096.

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This paper focuses on designing a facility network, taking into account that the system may be congested. The objective is to minimize the overall fixed and service capacity costs, subject to the constraints that for any demand the disutility from travel and waiting times (measured as the weighted sum of the travel time from a demand to the facility serving that demand and the average waiting time at the facility) cannot exceed a predefined maximum allowed level (measured in units of time). We develop an analytical framework for the problem that determines the optimal set of facilities and assigns each facility a service rate (service capacity). In our setting, the consumers would like to maximize their utility (minimize their disutility) when choosing which facility to patronize. Therefore, the eventual choice of facilities is a user-equilibrium problem, where at equilibrium, consumers do not have any incentive to change their choices. The problem is formulated as a nonlinear mixed-integer program. We show how to linearize the nonlinear constraints and solve instead a mixed-integer linear problem, which can be solved efficiently.
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15

Aslam, Sheraz, Michalis P. Michaelides, and Herodotos Herodotou. "Berth Allocation Considering Multiple Quays: A Practical Approach Using Cuckoo Search Optimization." Journal of Marine Science and Engineering 11, no. 7 (June 24, 2023): 1280. http://dx.doi.org/10.3390/jmse11071280.

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Maritime container terminals (MCTs) play a fundamental role in international maritime trade, handling inbound, outbound, and transshipped containers. The increasing number of ships and containers creates several challenges to MCTs, such as congestion, long waiting times before ships dock, delayed departures, and high service costs. The berth allocation problem (BAP) concerns allocating berthing positions to arriving ships to reduce total service cost, waiting times, and delays in vessels’ departures. In this work, we extend the study of continuous BAP, which considers a single quay (straight line) for berthing ships, to multiple quays, as found in many ports around the globe. Multi-Quay BAP (MQ-BAP) adds the additional dimension of assigning a preferred quay to each arriving ship, rather than just specifying the berthing position and time. In this study, we address MQ-BAP with the objective of minimizing the total service cost, which includes minimizing the waiting times and delays in the departure of ships. MQ-BAP is first formulated as a mixed-integer linear problem and then solved using the cuckoo search algorithm (CSA), a computational intelligence (CI)-based approach. In addition, the exact mixed-integer linear programming (MILP) method, two other state-of-the-art metaheuristic approaches, namely the genetic algorithm (GA) and particle swarm optimization (PSO), as well as a first come first serve (FCFS) approach, are also implemented for comparison purposes. Several experiments are conducted using both randomly generated and real data from the Port of Limassol, Cyprus, which has five quays serving commercial vessel traffic. The comparative analysis and experimental results show that the CSA-based method achieves the best overall results in affordable time as compared to the other CI-based methods, for all considered scenarios.
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Xu, Wei, Chenghao Zhang, Ming Cheng, and Yucheng Huang. "Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery: Mathematical Modeling and Adaptive Large Neighborhood Search Heuristic Method." Energies 15, no. 23 (December 5, 2022): 9222. http://dx.doi.org/10.3390/en15239222.

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Electric vehicles (EVs) are a promising option to reduce air pollution and shipping costs, especially in urban areas. To provide scientific guidance for the growing number of logistics companies using EVs, we investigated an electric-vehicle-routing problem with simultaneous pickup and delivery that also considers non-linear charging and load-dependent discharging (EVRPSPD-NL-LD). The objective was to minimize the total number of EVs and the total working time, including travel time, charging time, waiting time, and service time. We formulated the problem as a mixed integer linear program (MILP), and small-size problems could be solved to optimality in an acceptable amount of time using the commercial solver IBM ILOG CPLEX Optimization Studio (CPLEX). In view of the fact that the problem is NP-hard, an adaptive large neighborhood search (ALNS) metaheuristic method was proposed to solve large-size problems. Meanwhile, new operators and a time priority approach were developed to provide options for different scenarios. The results of our computational investigation and sensitivity analysis showed that the proposed methods are effective and efficient for modified benchmark instances.
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Syahraini, Syahraini, Syahril Efendi, and Syahriol Sitorus. "A Decision Model For Tackling Logistic Optimization Problem in Online Business Environment." SinkrOn 7, no. 3 (August 12, 2022): 2038–43. http://dx.doi.org/10.33395/sinkron.v7i3.11593.

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Online business has increased during the COVID-19 pandemic, but the emergence of a number of problems, namely reduced material supply, price fluctuations because an item is difficult to distribute and slow delivery due to transportation of goods based on the type of transportation used (Trucks, Trains, Airplanes and Ships). a number of declines due to the COVID-19 virus pandemic, resulting in longer order waiting times. Pick-up and Delivery Issues are variations of Vehicle Routing Issues that appear in many real-world transportation scenarios, such as product delivery and courier services. This work studies the Pickup and Delivery Problem with Time Windows, where goods must be transported from one location to another, with taking into account certain time limits and vehicle capacity. This aims to minimize the number of vehicles used, as well as operational costs for all routes. To solve this problem, a mathematical model in the form of is used Mixed Integer Linear Programming (MILP) from Pickup and Delivery Problems with Time Windows
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Kovač, Nataša, Tatjana Davidović, and Zorica Stanimirović. "Population-based Metaheuristics for the Dynamic Minimum Cost Hybrid Berth Allocation Problem." International Journal on Artificial Intelligence Tools 30, no. 04 (June 2021): 2150017. http://dx.doi.org/10.1142/s0218213021500172.

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This study considers the Dynamic Minimum Cost Hybrid Berth Allocation Problem (DMCHBAP) with fixed handling times of vessels. The objective function to be minimized consists of three components: costs of positioning, waiting, and tardiness of completion for all vessels. A mathematical formulation of DMCHBAP, based on Mixed Integer Linear Programming (MILP), is proposed and used within the framework of commercial CPLEX 12.3 solver. As the speed of finding high-quality solutions is of crucial importance for an efficient and reliable decision support system in container terminal, two population-based metaheuristic approaches to DMCHBAP are proposed: combined Genetic Algorithm (cGA) and improvement-based Bee Colony Optimization (BCOi). Both cGA and BCOi are evaluated and compared against each other and against state-of-the-art solution methods for DMCHBAP on five sets of problem instances. The conducted computational experiments and statistical analysis indicate that population-based metaheuristic methods represent promising approaches for DMCHBAP and similar problems in maritime transportation.
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Rifai, Andri Irfan, Martindo Gita Dwi Putra, Muhammad Isradi, Amar Mufhidin, and Joewono Prasetijo. "Evaluation of Selection of Public Transport Mode Corridor Blok M – Bundaran Hotel Indonesian in the New Normal Era with Stated Preference." IJEBD (International Journal of Entrepreneurship and Business Development) 5, no. 4 (July 31, 2022): 792–805. http://dx.doi.org/10.29138/ijebd.v5i4.1916.

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Purpose: Transportation is one of the important things in supporting community activities outside the home. Currently, people are faced with the new normal era so they have to adapt to new things due to the COVID-19 pandemic outbreak. This study wants to know about the behavior of the community in the selection of public transportation in the corridor Blok M – Bundaran Hotel Indonesia in the new normal era. Design/methodology/approach: Data were obtained from the results of a questionnaire survey of users of the Blok M – Bundaran Hotel Indonesia public transport corridor using stated preference methods and used influence attributes in the form of travel costs, travel time, and waiting time. The survey results were collected and then linear regression analysis was performed and modeling was performed using the binomial logit model. Data analysis was carried out from questionnaire data distributed to 100 respondents. Findings: The survey results were collected and then linear regression analysis was performed and modeling was performed using the binomial logit model. Data analysis was carried out from questionnaire data distributed to 100 respondents. The results of linear regression analysis using the SPSS program obtained a mode selection model, namely (UMRT-UTJ) = -2.331 + 0.000X1 + 0.040X2 + 0.820X3, where X1 is the travel cost variable, X2 is the travel time variable and X3 is the waiting time variable. The conclusion obtained from the results of this study is that the MRT is the most preferred mode of public transportation compared to Transjakarta in this new normal era. Research limitations/implications: Although most of the enterprises surveyed have an idea how to respond to calamities and mitigate disastrous situations, this research argues that a solid policy framework might be drawn through the local government units concerned to institutionalized this effort. Practical implications: The convenience factor is the main factor for public transport users to choose the MRT, while the travel cost factor is the main factor for public transport users to choose Transjakarta. Originality/value: This paper is an original work. Paper type: Research paper
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Shi, Ying, Xin Li, and Ping Fan. "Optimization of an M/M/∞ Queueing System with Free Experience Service." Asia-Pacific Journal of Operational Research 33, no. 06 (December 2016): 1650051. http://dx.doi.org/10.1142/s0217595916500512.

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It is a common practice for online service providers to offer free experience service to attract new clients. However, providing experience service requires resources, which may negatively impact current service level and lead to customer turnover. Therefore, providers need to trade off between consequent benefits and costs. We consider a free experience service system where each arriving customer can start his service immediately without waiting, which is a typical situation of many online service platforms. A queueing model with infinite number of servers is employed to study such a service system. The closed forms of the expected numbers of informed and uninformed customers in steady-state are derived by solving nonhomogeneous linear partial differential equations. After that, the expected profit of the service provider is generated and maximized by determining the optimal price and service rates. Our numerical results suggest that with the increase of the market share and the serving cost for the informed customers, the service provider should lay more emphasis on offering the regular service for the informed customers.
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You, Peng-Sheng, and Yi-Chih Hsieh. "A heuristic algorithm for medical staff’s scheduling problems with multiskills and vacation control." Science Progress 104, no. 3_suppl (July 2021): 003685042110503. http://dx.doi.org/10.1177/00368504211050301.

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Introduction The main issue related to the duty schedule is to allocate medical staff to each medical department by considering personnel skills and personal vocation preferences. However, how to effectively use staff’s multiskill characteristics and how to execute vocation control have not been well investigated. Objectives This article aims to develop duty scheduling and vacation permission decisions to minimize the sum of customers’ waiting costs, the overtime cost of medical staff, the cost of failing to meet medical staff’ vacation requirements, and the cost of mutual support between departments. Methods This study formulated the problem as a multiperiod mixed integer nonlinear programming model and developed a hybrid heuristic based on evolutionary mechanism of genetic algorithm and linear programming to efficiently solve the proposed model. Results Five types of problems were solved through Lingo optimization and the proposed approach. For small-scale problems, both methods can find the optimal solutions. For a slightly larger problem, the solutions found by the proposed approach are superior those of Lingo. Conclusion This research discusses the complex decision-making problem of on-duty arrangement and vacation control of medical staff in a multidepartmental medical center. This research formulates the medical staff’s scheduling and vacation control problems as constrained mixed integer quadratic programming problems. Computational results indicate that the proposed approach can efficiently produce compromise solutions that outperform the solutions of the Lingo optimization software.
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Zhan, Xiangnan, Liyun Xu, and Xufeng Ling. "Task Scheduling Problem of Double-Deep Multi-Tier Shuttle Warehousing Systems." Processes 9, no. 1 (December 26, 2020): 41. http://dx.doi.org/10.3390/pr9010041.

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Double-deep multi-tier shuttle warehousing systems (DMSWS) have been increasingly applied for store-and-retrieval stock-keeping unit tasks, with the advantage of a reduced number of aisles and improved space utilization. Scheduling different devices for retrieval tasks to increase system efficiency is an important concern. In this paper, a Pareto optimization model of task operations based on the cycle time and carbon emissions is presented. The impact of the rearrangement operation is considered in this model. The cycle time model is converted into a flow-shop scheduling model with parallel machines by analyzing the retrieval operation process. Moreover, the carbon emissions of the shuttle in the waiting process, the carbon emissions of the lift during the free process, and the carbon emissions of the retrieval operation are considered in the carbon emissions model, which can help us to evaluate the carbon emissions of the equipment more comprehensively during the entire retrieval task process. The elitist non-dominated sorting genetic algorithm II (NSGA-II) is adopted to solve the non-linear multi-objective optimization function. Finally, a real case is adopted to illustrate the findings of this study. The results show that this method can reduce carbon emissions and improve system efficiency. In addition, it also help managers to reduce operational costs and improve the utilization of shuttles.
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Kong, Qingxia, Shan Li, Nan Liu, Chung-Piaw Teo, and Zhenzhen Yan. "Appointment Scheduling Under Time-Dependent Patient No-Show Behavior." Management Science 66, no. 8 (August 2020): 3480–500. http://dx.doi.org/10.1287/mnsc.2019.3366.

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This paper studies how to schedule medical appointments with time-dependent patient no-show behavior and random service times. The problem is motivated by our studies of independent datasets from countries in two continents that unanimously identify a significant time-of-day effect on patient show-up probabilities. We deploy a distributionally robust model, which minimizes the worst-case total expected costs of patient waiting and service provider’s idling and overtime, by optimizing the scheduled arrival times of patients. This model is challenging because evaluating the total cost for a given schedule involves a linear program with uncertainties present in both the objective function and the right-hand side of the constraints. In addition, the ambiguity set considered contains discrete uncertainties and complementary functional relationships among these uncertainties (namely, patient no-shows and service durations). We show that when patient no-shows are exogenous (i.e., time-independent), the problem can be reformulated as a copositive program and then be approximated by semidefinite programs. When patient no-shows are endogenous on time (and hence on the schedule), the problem becomes a bilinear copositive program. We construct a set of dual prices to guide the search for a good schedule and use the technique iteratively to obtain a near-optimal solution. Our computational studies reveal a significant reduction in total expected cost by taking into account the time-of-day variation in patient show-up probabilities as opposed to ignoring it. This paper was accepted by David Simchi-Levi, optimization.
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Jenny, Hillary, Maria Reategui Via y Rada, Pooja Yesantharao, Helen Xun, Richard Redett, Justin Michael Sacks, and Robin Yang. "Efficacy of a Novel Intraoperative Engineered Sharps Injury Prevention Device: Pilot Usability and Efficacy Trial." JMIR Perioperative Medicine 3, no. 2 (November 27, 2020): e19729. http://dx.doi.org/10.2196/19729.

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Background The American College of Surgeons reports 88,320 intraoperative needlestick injuries (NSIs) per year, resulting in US $376 to US $2456 in costs per NSI. Engineered sharps injury prevention (ESIP) devices protect against NSIs. To our knowledge, no study has been published to date to demonstrate clinical effectiveness of an intraoperative ESIP device. Operative Armour is a wearable arm cuff that can be donned during surgical closure to allow surgeons to keep a suture pack and sharps protection container on their forearm. Objective We characterize Operative Armour’s ESIP device effectiveness in a tertiary hospital, hypothesizing that this device will decrease NSI risk by decreasing behaviors associated with NSIs: needle passing and handling. Methods A prospective case-control study was conducted with institutional review board quality improvement designation in which authors observed skin closures of plastic surgery procedures. To ensure accuracy, one surgeon was observed at a time. Control surgeries were purely observational; intervention cases involved surgeon use of the device during skin closure. Outcomes of interest included needle passing, needle handling, lost needles, and loaded waiting needles. Results Surgeons were observed in 50 control and 50 intervention cases. Operative Armour eliminated needle passing during skin closure. One NSI occurred in one control case; no NSIs were observed in intervention cases (P=.36). The mean number of loaded and unprotected waiting needles was also significantly decreased in the intervention group from 2.3 to 0.2 (P<.001). Furthermore, a multivariable linear regression established that Operative Armour significantly decreased the number of needle adjustments by hand per stitch observed (F4, 21.68=3.72; P=.01). In fact, needle adjustments by hand decreased overall (1 adjustment per 10 stitches vs 1 adjustment per 5 stitches, P=.004), and adjustments occurred half as frequently with use of Operative Armour in free flap reconstruction (1 adjustment per 10 stitches vs 1 adjustment per 5 stitches, P=.03) and a quarter as frequently in other breast reconstruction cases such as mastopexy (1 adjustment per 20 stitches vs 1 adjustment per 5 stitches, P=.002). Conclusions Operative Armour effectively functions as an ESIP device by decreasing intraoperative needle passing and handling. Although sample size prohibits demonstrating a decrease in NSIs during observed cases, by decreasing behaviors that drive NSI risk, we anticipate an associated decrease in NSIs with use of the device.
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Terglav, Barbara Zupanc, Špela Selak, Mitja Vrdelja, Boris Miha Kaučič, and Branko Gabrovec. "Patient satisfaction with the level of being informed about the changes in Slovenian healthcare system." Pielegniarstwo XXI wieku / Nursing in the 21st Century 18, no. 1 (March 1, 2019): 37–41. http://dx.doi.org/10.2478/pielxxiw-2019-0003.

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AbstractIntroduction. Patients’ satisfaction has a very important role regarding reforms of the healthcare system, which aim at improvement of health and optimisation of costs. Informed patient is one of the factors which notably influences patients’ satisfaction.Aim. To determine the level of satisfaction of Slovenian residents with the current healthcare system and how well informed they are about the draft law changes to the Healthcare and Health Insurance Act, debated in public in 2017.Methods. A descriptive, non-experimental sampling method was used (snowball method). A structured questionnaire was used as a measurement tool. The number of 488 persons finished the entire online questionnaire. The data were analysed using the SPSS programme, version 21 (significance level p<0.05), and using descriptive statistics, correlation analysis, t-test and linear regression analysis.Results. Slovenian residents are fairly (un)satisfied with the current healthcare system. Waiting lines affect satisfaction with the current health care system the most, followed by the level of trust in a doctor’s decision concerning treatment and the level of respectfulness in the communication of healthcare workers with patients. Although respondents are less informed about the proposed changes, they support the draft law changes to a high degree. They perceive the information provided on the proposed changes in healthcare as relatively understandable and evaluate them positively. Television is the most important source of information on law changes in healthcare.Discussion and conclusions. Slovenian residents support the public healthcare system to a very high degree and are less in favour of private healthcare. In the future, more attention needs to be directed towards the related strategic communication and the choice of communication channels with the planned changes in healthcare.
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Goedeke, Sonja, Daniel Shepherd, and Iolanda S. Rodino. "Support for recognition and payment options for egg and sperm donation in New Zealand and Australia." Human Reproduction 35, no. 1 (January 1, 2020): 117–29. http://dx.doi.org/10.1093/humrep/dez257.

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Abstract STUDY QUESTION To what extent do infertility clinic patients, fertility industry professionals and members of the public support different forms of payment and recognition for egg and sperm donation? SUMMARY ANSWER While participants expressed support for reimbursement of expenses for both egg and sperm donation, payment constituting explicit financial advantage was regarded less favourably although potentially necessary to address donor gamete shortages. WHAT IS KNOWN ALREADY In both New Zealand and Australia, commercial inducement for the supply of gametes is prohibited. This prohibition has been argued to contribute to limited availability of donor gametes with the effect of increasing waiting lists and/or the pursuit of potentially unregulated cross-border reproductive care by domestic patients requiring donor gametes. STUDY DESIGN, SIZE, DURATION The study was a mixed methods study drawing on data from a questionnaire completed by 434 participants from across New Zealand and Australia between November 2018 and March 2019. PARTICIPANTS/MATERIALS, SETTING, METHODS Stakeholders involved in donor-assisted conception (past and present infertility patients, gamete recipients and donors), fertility industry professionals and members of the public were recruited following online advertisement of the study. All participants spoke English and primarily identified as Caucasian. Participants anonymously completed an online questionnaire gauging their support for a range of recognition and payment options. Dependent samples t-tests were used to probe for differences in support of recognition and payment options in relation to egg and sperm donation. Linear regression models were used to determine factors predicting support for the different options for both egg and sperm donation. Thematic analysis was used to identify main themes in free text question responses. MAIN RESULTS AND THE ROLE OF CHANCE Broadly, there was agreement that donors be reimbursed for medical expenses, travel time, unpaid time away from work relating to treatments and out-of-pocket expenses directly related to the gamete donation process, with greater support suggested for egg versus sperm donors. Items gauging support for non-material recognition and tokens of thanks for donations were not significantly different between egg and sperm donation programmes (P &gt; 0.05) nor rated as highly as reimbursement alternatives. Lowest ratings of support were indicated for the outright payment or reward of donors for the supply of their gametes, options that would leave donors in better financial positions. Qualitatively, themes valuing gamete donation as ideally relating to gifting were identified, although counterbalanced in opinion by concepts of fairness in reimbursing gamete donors for their costs. Where payment over and above the reimbursement of costs was supported, this was related to pragmatic considerations of limited supply of donor gametes. LIMITATIONS, REASONS FOR CAUTION This study used a cross-sectional design and consequently causal inferences cannot be made. Additionally, participants particularly professional fertility staff, were required to self-report on politically sensitive and legal issues with the potential for social desirability response bias. Snowball sampling may have led to participation of like-minded individuals, thus limiting generalizations of findings. WIDER IMPLICATIONS OF THE FINDINGS In a climate of global commercialization of reproductive medicine, limited donor gamete availability and rising incidences of cross-border reproductive care, the findings of this study can be used as a basis for further discussion between regulators and professional industry stakeholders with respect to shaping ethical policy and practice relating to donor conception. STUDY FUNDING/COMPETING INTEREST(S) No external funds were sought for this work. None of the authors have any competing interests to declare. TRIAL REGISTRATION NUMBER N/A.
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Burra, Ramya, Chandramani Singh, and Joy Kuri. "Service Scheduling for Random Requests with Deadlines and Linear Waiting Costs." IEEE Transactions on Network Science and Engineering, 2021, 1. http://dx.doi.org/10.1109/tnse.2021.3091763.

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28

Lacowicz, Pedro Giovani, Ricardo Berger, Romano Timofeiczyk Júnior, and João Carlos Garzel Leodoro Da Silva. "MINIMIZAÇÃO DOS CUSTOS DE TRANSPORTES RODOVIÁRIO FLORESTAL COM O USO DA PROGRAMAÇÃO LINEAR E OTIMIZAÇÃO DO PROCESSO." FLORESTA 32, no. 1 (June 30, 2002). http://dx.doi.org/10.5380/rf.v32i1.2350.

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Este trabalho tratou da minimização dos custos do transporte rodoviário florestal, através da programação linear inteira e otimização dos tempos de ciclo de transporte. Após a obtenção dos dados de uma empresa florestal, foram elaborados três cenários, quais sejam: Cenário I: levantamento do quadro atual da empresa, como subsídio comparativo após a racionalização e otimização das etapas que mais consomem tempo do ciclo; Cenário II: realizada em função do uso da programação linear, juntamente com a racionalização dos tempos de fila de espera para carga e descarga; Cenário III: além da programação linear e racionalização dos tempos de espera em fila, utilizou-se, paralelamente, uma otimização do tempo de carga e uma elevação da velocidade de transporte. Os resultados mostraram-se significativos, onde a racionalização e a otimização contribuíram para a redução no número de caminhões e do custo total, traduzindo-se em aumentos na produção dos veículos, na receita bruta e líquida dos freteiros. Cost Minimization of Forest Road Transport by Using the Integer Linear Program and Transport Cycle Time Optimization Abstract This study was about the decreasent of the costs of forest road transport, using the integer linear program and transport cycle time optimization. After obtaining all of the costs, consumed time and the current company picture, a total of three evaluations were done and are described below in settings. Setting I: The current company picture data was calculated as a comparative subsidy following the racionalization and optimization stages that are more time-consuming in the transport cycle. Setting II: This evaluation was done in terms of linear programation use, together with the loading and unloading waiting in line time racionalization. Setting III: In this evaluation, besides the linear programation use and waiting in line time racionalization, it was simultaneously used a time optimization and a foster transport speed. The acquired results were very meaningful, while the racionalization and optimization happened, the trucks rate and total cost successively decreased, resulting in better vehicles performance, and consequently, an increase in the gross and net drivers’ income. Even though there was a costs decrease and an outsiders’ income increase, wich was not enough to pay their total costs, that is, only the variable ones were totally paid and part of the outsiders’ fixed cost.
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Scala, Arianna, Anna Borrelli, and Giovanni Improta. "Predictive analysis of lower limb fractures in the orthopedic complex operative unit using artificial intelligence: the case study of AOU Ruggi." Scientific Reports 12, no. 1 (December 22, 2022). http://dx.doi.org/10.1038/s41598-022-26667-0.

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AbstractThe length of stay (LOS) in hospital is one of the main parameters for evaluating the management of a health facility, of its departments in relation to the different specializations. Healthcare costs are in fact closely linked to this parameter as well as the profit margin. In the orthopedic field, the provision of this parameter is increasingly complex and of fundamental importance in order to be able to evaluate the planning of resources, the waiting times for any scheduled interventions and the management of the department and related surgical interventions. The purpose of this work is to predict and evaluate the LOS value using machine learning methods and applying multiple linear regression, starting from clinical data of patients hospitalized with lower limb fractures. The data were collected at the "San Giovanni di Dio e Ruggi d’Aragona" hospital in Salerno (Italy).
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30

Caicedo-Rolón Junior, Álvaro, and John Wilmer Parra Llanos. "Production sequencing in a flow shop system using optimization and heuristic algorithms." Gestão & Produção 28, no. 1 (2021). http://dx.doi.org/10.1590/1806-9649.2020v28e3886.

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abstract: The purpose of the research was to determine the sequencing of the production of n jobs in m operations in a small footwear company in an environment of flow shop machine characteristics, which optimizes the total time of completion of the job in the production system (Makespan). We used heuristic algorithms that were applied through Lekin and WinQSB softwares, and for the optimization algorithm we designed a mathematical model that was solved by Juliabox software. Results show that the integer linear programming and local search minimize the makespan with 3807 minutes, and different production sequences for each algorithm, which consider permutation, which improves the traditional way of programming the production in 97 minutes, however, the optimization presents better results in the performance measures of average waiting time, average time of flow, and average job in process. Application of heuristic algorithms proves to be simple and fast, but the mathematical model of optimization designed and encoded in the software is a flexible and valuable tool for decision making in production programming, which could be applied in other footwear companies, and in other productive sectors whose companies have the same characteristics of the case study, reducing costs and improving delivery times.
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31

Li, Xiulin, Jiansha Lu, Chenxi Yang, and Jiale Wang. "Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony." Frontiers in Bioengineering and Biotechnology 10 (August 16, 2022). http://dx.doi.org/10.3389/fbioe.2022.909548.

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This study examined the flexible assembly job-shop scheduling problem with lot streaming (FAJSP-LS), common in multivariety and small-batch production, such as household electrical appliances. In FAJSP-LS, an assembly stage is appended to the flexible job shop, and jobs in the first stage are processed in a large batch to reduce switching costs, while leading to more waiting time, especially during the assembly stage. This article considered splitting the batch into a few sub-batches of unequal and consistent sizes to allow jobs to efficiently pass the two-stage system. With this objective, the problem was modeled as a mixed-integer linear program comprising the following two subproblems: batch splitting and batch scheduling. As the integrated problem is NP-hard, the improved bioinspired algorithm based on an artificial bee colony was proposed, including a four-layer chromosome–encoding structure to describe the solution, as well as an optimization strategy utilizing different bee colonies to synchronously solve this two-stage problem. To examine the algorithm’s efficiency, a benchmark case was used to show that better solutions can be acquired with the improved algorithm regardless of whether the batch was split into equal or unequal sizes. To promote practical implementation, the algorithm was applied to a real case refrigerator workshop and showed better performance on time efficiency when jobs were split into unequal sizes compared to jobs without splitting or splitting into equal sizes.
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32

Yuhua, Yang, Samà Marcella, Pacciarelli Dario, and Ni Shaoquan. "Train timetabling with passenger data and heterogeneous rolling stocks circulation on urban rail transit line." Soft Computing, May 5, 2022. http://dx.doi.org/10.1007/s00500-022-07057-0.

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AbstractThe planning process in urban rail transportation can be split into several stages, including line planning, timetabling, rolling stock scheduling and so on. The outcome of a stage provides inputs or constraints to the subsequent ones. However, while the output can be good or optimal at each stage, it rarely considers the global quality for the overall planning process. Furthermore, problems tackled at planning phase often use a more aggregate representation of reality, to achieve a more general overview. An integrated approach, while more complex to solve, may mitigate the gap between solution of different stages and a validation of a plan would still be required before its implementation in practice. In this paper, we focus on integrated optimization of train timetabling and rolling stock circulation for urban rail transit line with time-based origin-destination-dependent passenger travel demand and heterogeneous rolling stocks. The aim is to generate a comfortable timetable for passengers and an efficient timetable for operators. The objective is to minimize the total waiting time for passengers and the costs for operators, while constraints regarding train movements, passenger boarding and alighting, available rolling stocks and their capacity are considered. A mixed integer linear programming model is formulated and solved by an iterative programming approach. Computational experiments are performed on the Chongqing Rail Transit Line 2 to verify the efficiency and effectiveness of the proposed model and solving method. With respect to CPLEX, results show the proposed iterative programming approach has advantages both on computation time and solution quality.
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Li, Xiaokun, and Xin Li. "Development of following robot for supplying power to solar panel cleaning robot." Industrial Robot: the international journal of robotics research and application ahead-of-print, ahead-of-print (July 27, 2021). http://dx.doi.org/10.1108/ir-03-2021-0055.

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Purpose Autonomous mobile cleaning robots are widely used to clean solar panels because of their flexibility and high efficiency. However, gravity is a challenge for cleaning robots on inclined solar panels, and robots have problems such as high working power and short battery life. This paper aims to develop a following robot to improve the working time and efficiency of the cleaning robot. Design/methodology/approach The mechanical structure of the robot is designed so that it can carry a large-capacity battery and continuously power the cleaning robot. The robot determines its position and orientation relative to the edge of solar panel by using optoelectronic sensors. Based on the following distance, the robot changes its state between moving and waiting to ensure that supply cable will not drag. Findings Prototype following robot test results show that the following robot can stably follow the cleaning robot and supply continuous power to cleaning robot. The linear error of the following robot moving along the solar panel is less than 0.3 m, and the following distance between the robot and the cleaning robot is in 0.5–1.5 m. Practical implications The working time of cleaning robots and working efficiency is improved by using following robot, thereby reducing the labor intensity of workers and saving the labor costs of cleaning. Originality/value The design of the following robot is innovative. Following robot works with the existing cleaning robots to make up for shortcomings of the existing cleaning system. It provides a more feasible and practical solution for using robots to clean solar panels.
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Greene, Andrew, and Christopher Miles. "Surgery avoidance rates among total knee replacement candidates following a non-invasive biomechanical intervention: A retrospective cohort study." Journal of Orthopaedic Experience & Innovation, October 6, 2022. http://dx.doi.org/10.60118/001c.37664.

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Background Nearly twenty million people are affected by osteoarthritis (OA) across the UK. For end-stage knee OA, total knee replacement (TKR) is considered as the standard of care, but this major surgery carries high costs, long waiting lists, and risk for further revision surgeries. Health systems are therefore looking for effective alternatives to treat these cohorts, significantly delaying, and potentially avoiding joint replacement surgery altogether. The purpose of this study was to examine the 2-year surgery avoidance rate amongst TKR candidates that received a non-invasive biomechanical intervention. Methods A retrospective clinical audit was conducted on 365 NHS patients with end-stage knee OA patients eligible for TKR. Each patient was individually fitted with a non-invasive, shoe-like, biomechanical device, that alters the foot center of pressure, minimizes reported symptoms, and promotes neuromuscular control training using convex pods under the sole. Patients used the device for short periods during activities of daily living and were followed for two years. The primary outcome was surgery status after 2 years. Secondary outcomes were evaluated using the generalized linear mixed-models procedure and included changes in pain, function (WOMAC and Oxford Knee Score (OKS), and spatiotemporal gait measured at 3, 6, 12, and 24 months from baseline. Results Of the 365 candidates for TKR, 305 (84%) avoided surgery at 2 years. Patients displayed significant clinical improvements over time. Six months after starting treatment, average pain decreased by 42%, average function improved by 39%, and average OKS increased by 7.6 points. These continued to improve over the 2 years. All spatial-temporal gait measures improved over time (p<0.001). Conclusions The current results suggest that a non-invasive biomechanical treatment may help end-stage knee OA patients delay knee replacement surgery for at least 2 years or avoid it altogether. This treatment may provide an effective non-surgical alternative for managing these patients in the community, alleviating pain, and improving gait and function.
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Marshman, Zoe, Helen Rodd, Caroline Fairhurst, Jenny Porritt, Bhupinder Dawett, Peter Day, Nicola Innes, et al. "The CALM trial protocol: a randomised controlled trial of a guided self-help cognitive behavioural therapy intervention to reduce dental anxiety in children." Trials 24, no. 1 (January 6, 2023). http://dx.doi.org/10.1186/s13063-022-07046-6.

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Abstract Background Globally, around 13% of children experience dental anxiety (DA). This group of patients frequently miss dental appointments, have greater reliance on treatment under general anaesthesia (GA) and have poorer oral health-related quality of life (OHRQoL) than their non-dentally anxious peers. Recently, a low-intensity cognitive behavioural therapy (CBT)-based, self-help approach has been recommended for management of childhood anxiety disorders. A feasibility study conducted in secondary care found this guided self-help CBT resource reduced DA and a randomised controlled trial was recommended. The present study aims to establish the clinical and cost-effectiveness of a guided self-help CBT intervention to reduce DA in children attending primary dental care sites compared to usual care. Methods This 4-year randomised controlled trial will involve 600 children (aged 9–16 years) and their parent/carers in 30 UK primary dental care sites. At least two dental professionals will participate in each site. They will be assigned, using random allocation, to receive the CBT training and deliver the intervention or to deliver usual care. Children with DA attending these sites, in need of treatment, will be randomly allocated to be treated either by the intervention (CBT) or control (usual care) dental professional. Children will complete questionnaires relating to DA, OHRQoL and HRQoL before treatment, immediately after treatment completion and 12 months post-randomisation. Attendance, need for sedation/GA and costs of the two different approaches will be compared. The primary outcome, DA, will be measured using the Modified Child Dental Anxiety Scale. Scores will be compared between groups using a linear mixed model. Discussion Treating dentally anxious patients can be challenging and costly. Consequently, these children are frequently referred to specialist services for pharmacological interventions. Longer waiting times and greater travel distances may then compound existing healthcare inequalities. This research will investigate whether the intervention has the potential to reduce DA and improve oral health outcomes in children over their life-course, as well as upskilling primary dental healthcare professionals to better manage this patient group. Trial registration This clinical trial has been registered with an international registry and has been allocated an International Standard Randomised Controlled Trial Number (ISRCTN27579420).
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