Daily Plan Research Articles

Pengembangan Kecerdasan Musikal Anak di Taman Kanak-Kanak Pertiwi 3 Kantor Gubernur Padang

This research is carried out every day the implementation of activities carried out in Kindergarten Pertiwi 3 Of the Padang Governor's Office held knock play activities in the classroom so that every day children feel interesting activities and do not get bored for children for the development of children's musical intelligence. This research aims to get an overview of the development of early childhood musical intelligence in Kindergarten Pertiwi 3 Padang Governor's Office. This type of research is qualitative research using a descriptive approach. To see how the development of early childhood musical intelligence in Kindergarten Pertiwi 3 Padang Governor's Office. The subjects of the study were B3-graders at Kindergarten 3 of the Padang Governor's Office. The informant of this study is the principal and teacher in Kindergarten Pertiwi 3 Of the Padang Governor's Office.
 Data collection techniques are used in the form of observations, interviews, and documentation. Data analysis techniques are: 1) data collection, 2) data reduction, 3) presentation of data, 4) verification. While the data absorbing technique used in the form of triangulation techniques. The results of the study in general showed that in the development of early childhood musical intelligence in Kindergarten 3 the Governor's Office of Padang teachers has prepared a Daily Learning Implementation Plan (RPPH). Activities carried out every day have been done in accordance with what has been planned, activities carried out every day using various activities such as, playing beats, singing and others. Furthermore, after the child conducts teacher activities to conduct evaluations by means of observation and daily assessment.

Generation and evaluation of anatomy-preserving virtual CT for online adaptive proton therapy.

Daily CTs generated by CBCT correction are required for daily replanning in online-adaptive proton therapy (APT) to effectively deal with inter-fractional changes. Out of the currently available methods, the suitability of a daily CT generation method for proton dose calculation also depends on the anatomical site. We propose an anatomy-preserving virtual CT (APvCT) method as a hybrid method of CBCT correction, which is especially suitable for large anatomy deformations. The accuracy of the hybrid method was assessed by comparison with the corrected CBCT (cCBCT) and virtual CT (vCT) methods in the context of online APT. Seventy-one daily CBCTs of four prostate cancer patients treated with intensity modulated proton therapy (IMPT) were converted to daily CTs using cCBCT, vCT, and the newly proposed APvCT method. In APvCT, planning CT (pCT) were mapped to CBCT geometry using deformable image registration with boundary conditions on controlling regions of interest (ROIs) created with deep learning segmentation on cCBCT. The relative frequency distribution (RFD) of HU, mass density and stopping power ratio (SPR) values were assessed and compared with the pCT. The ROIs in the APvCT and vCT were compared with cCBCT in terms of Dice similarity coefficient (DSC) and mean distance-to-agreement (mDTA). For each patient, a robustly optimized IMPT plan was created on the pCT and subsequent daily adaptive plans on daily CTs. For dose distribution comparison on the same anatomy, the daily adaptive plans on cCBCT and vCT were recalculated on the corresponding APvCT. The dose distributions were compared in terms of isodose volumes and 3D global gamma-index passing rate (GPR) at γ(2%, 2mm) criterion. For all patients, no noticeable difference in RFDs was observed amongst APvCT, vCT, and pCT except in cCBCT, which showed a noticeable difference. The minimum DSC value was 0.96 and 0.39 for contours in APvCT and vCT respectively. The average value of mDTA for APvCT was 0.01cm for clinical target volume and ≤0.01cm for organs at risk, which increased to 0.18cm and ≤0.52cm for vCT. The mean GPR value was 90.9%, 64.5%, and 67.0% for APvCT versus cCBCT, vCT versus cCBCT, and APvCT versus vCT, respectively. When recalculated on APvCT, the adaptive cCBCT and vCT plans resulted in mean GPRs of 89.5±5.1% and 65.9±19.1%, respectively. The mean DSC values for 80.0%, 90.0%, 95.0%, 98.0%, and 100.0% isodose volumes were 0.97, 0.97, 0.97, 0.95, and 0.91 for recalculated cCBCT plans, and 0.89, 0.88, 0.87, 0.85, and 0.81 for recalculated vCT plans. Hausdorff distance for the 100.0% isodose volume in some cases of recalculated cCBCT plans on APvCT exceeded 1.00cm. APvCT contours showed good agreement with reference contours of cCBCT which indicates anatomy preservation in APvCT. A vCT with erroneous anatomy can result in an incorrect adaptive plan. Further, slightly lower values of GPR between the APvCT and cCBCT-based adaptive plans can be explained by the difference in the cCBCT's SPR RFD from the pCT.

Customized GRASP for rehabilitation therapy scheduling with appointment priorities and accounting for therapist satisfaction

Physical therapy in acute care hospitals plays an important role in the rehabilitation of patients. Nevertheless, the profession must deal with staff shortages caused by a lack of potential employees and absenteeism which are results of high physical and mental workloads. The therapist shortage negatively affects the total number of daily appointments the department can fulfill. For appointments that can be successfully scheduled, continuity of care with the same therapist cannot be guaranteed for individual patients. Lack of continuity of care negatively influences the therapist's satisfaction. Therapist preferences for individual appointments in general cannot always be guaranteed when designing schedules, which also hurts satisfaction. This paper develops a multi-criteria model for the daily therapy appointment-scheduling problem. The primary objective is to minimize the total sum of priority violations for unscheduled appointments. To improve therapist satisfaction, we consider therapist preferences including continuity of care as a secondary objective. Here, our integer programming formulation aims to minimize the total sum of preference violations for scheduled appointments. We are dealing with an operational planning problem with a daily planning horizon. The operational objective is to achieve therapist schedules in at most two hours. The therapists’ schedules together need to include several hundred appointments for a planning day. Due to intractability, the developed integer program cannot provide schedules for such problem sizes. Therefore, we develop a customized Greedy Randomized Adaptive Search Procedure (GRASP) with six innovative local search operations to improve an initially constructed solution. We test the heuristic algorithm on realistic data instances. The metaheuristic provides high-quality schedules for various problem sizes in short runtimes, i.e., within minutes. Comparisons with the optimal solutions for small problem instances show very good results of the GRASP with a similar number of scheduled appointments and good adherence to continuity of care and therapist preference requirements.

Adaptive Radiotherapy for Bladder Cancer – A Review

Radiotherapy plays an important role in organ preservation for bladder cancer. Delivering radiation accurately can be challenging, in part because the bladder and surrounding organs may change position, volume, and shape between and during the fractions of a treatment course. This variability has been accounted for by increasing the margins around the treatment targets, which can expose more normal tissue to radiation, and increase the likelihood of normal tissue complications. An alternative strategy is to alter, or adapt, the radiotherapy treatment plan to account for such inter-fraction changes, a strategy termed ‘adaptive radiotherapy’ (ART). ART allows smaller target volumes to be treated, and may reduce complications. Approaches to ART include offline adaptation strategies and online strategies, which includes choosing a plan of the day (PoD) based on pre-treatment imaging and magnetic resonance (MR), or with cone-beam CT (CBCT)-guided daily plan re-optimisation. Here, the authors review these ART strategies and trials exploring the dosimetric and clinical benefits of ART relative to non-ART bladder radiotherapy.

Two-stage coordinated optimal dispatching model and benefit allocation strategy for rural new energy microgrid

To aggregate rural biomass energy, distributed power supply, flexibility load, and other resources, a novel structure of the rural Biomass-derived Fuel -based new energy microgrid (BDF-NEM) is proposed. It includes the Biomass Waste Conversion System (BWS), Distributed Renewable Energy (DRE), and Flexible Load Cluster (FLC). The two-stage scheduling optimization framework is designed for the BDF-NEM, minimizing operating costs in the Day-ahead phase and system deviation costs in the Intra-day phase. Uncertainty analysis of wind power plant (WPP) and photovoltaic generators (PV) is conducted using Latin hypercube sampling and the Kantorovich distance approach. To guarantee the equitable allocation of benefits, a benefit allocation mechanism grounded in the enhanced Sharp value approach takes into account operational risks. The analysis of a rural area in northern China demonstrates: (1) After BDF - NEM joined the tiered carbon trading mechanism, although it increased carbon trading costs by 31.27 %, wind power and photovoltaic output increased by 36.08 %, improving new energy consumption; (2) The two-stage scheduling optimization model with daily plan and daily correction can effectively alleviate the deviation caused by wind and solar uncertainty. Although the adjustment cost is 3966.41 yuan, it can avoid the penalty of load loss; (3) The improved benefit allocation based on the Shapley value method reflects the marginal contribution of each system module at the risk level, and when the system modules cooperate with each other, the return is 18.17 % higher than when operating alone, effectively stimulating the enthusiasm to participate in transactions. In summary, the BDF NEM proposed in this article can improve the utilization rate of wind and solar energy, promote the low-carbon development of rural power plants, and achieve local resource allocation in rural areas.

Integration of Google Maps API with mathematical modeling for solving the Real-Time VRP

Freight transportation is the backbone of urban economies and plays a critical role in the smooth functioning of cities. As such, devising efficient methods for freight transportation planning is of paramount importance. One of the most crucial aspects affecting the efficiency of freight transport is the variability in travel speeds, impacted by factors such as traffic congestion. While traditional approaches often rely on GPS technologies and associated routing services—which can be expensive—for planning, these methods also necessitate frequent re-optimization due to ever-changing traffic conditions. To address these challenges, we introduce a novel solution that integrates real-time traffic data into daily vehicle route planning. Specifically, our method incorporates Google Maps API for traffic congestion estimation and utilizes a Mixed Integer Linear Programming (MILP) model to determine optimal routes for an entire day. We tested our methodology in a major U.S. city and found that it outperforms conventional approaches by up to 18% in terms of routing time, underscoring its practical relevance and efficiency.

Методика разработки суточных планов интервалов движения пассажирских автотранспортных средств по городским регулярным маршрутам

Currently, the effectiveness of the influence of vehicle movement intervals on transport work has not been properly investigated. In addition, the rules for the formation of periods for the performance of transport work require further study. In this regard, the development of daily interval plans for passenger vehicles on urban regular routes becomes relevant. The article proposes a system of criteria for combining indicators of the passenger transportation process during periods of the day. This system is aimed at minimizing the value of the sum of the differences between the adjusted timetable and the estimated number of buses, taking into account work throughout all periods of the day, as well as ensuring the values of capacity utilization coefficients less than or equal to one. Based on the criteria system, an algorithm for developing daily interval plans for motor vehicles on urban regular routes has been obtained. The dependences have been established which demonstrate the sum values of the differences between the adjusted and calculated number of buses during all periods of the day along the route on the value of the adjustment interval. The dependencies have a minimum extremum, indicating the presence of an optimal peak interval.

Impact of daily plan adaptation on accumulated doses in ultra-hypofractionated magnetic resonance-guided radiation therapy of prostate cancer

Background and purposeUltra-hypofractionated online adaptive magnetic resonance-guided radiotherapy (MRgRT) is promising for prostate cancer. However, the impact of online adaptation on target coverage and organ-at-risk (OAR) sparing at the level of accumulated dose has not yet been reported. Using deformable image registration (DIR)-based accumulation, we compared the delivered adapted dose with the simulated non-adapted dose. Materials and methodsTwenty-three prostate cancer patients treated at two clinics with 0.35 T magnetic resonance-guided linear accelerator (MR-linac) following the same treatment protocol (5×7.5 Gy with urethral sparing and daily adaptation) were included. The fraction MR images were deformably registered to the planning MR image. Both non-adapted and adapted fraction doses were accumulated with the corresponding vector fields. Two DIR approaches were implemented. PTV* (planning target volume minus urethra+2mm) D95%, CTV* (clinical target volume minus urethra) D98%, and OARs (urethra+2mm, bladder, and rectum) D0.2cc, were evaluated. Statistical significance was inferred from a two-tailed Wilcoxon signed-rank test (p < 0.05). ResultsNormalized to the baseline, the accumulated PTV* D95% increased significantly by 2.7 % ([1.5, 4.3]%) through adaptation, and the CTV* D98% by 1.2 % ([0.1, 1.7]%). For the OARs after adaptation, accumulated bladder D0.2cc decreased by 0.4 % ([−1.2, 0.4]%), urethra+2mmD0.2cc by 0.8 % ([−1.6, −0.1]%), while rectum D0.2cc increased by 2.6 % ([1.2, 4.9]%). For all patients, rectum D0.2cc was still below the clinical constraint. Results of both DIR approaches differed on average by less than 0.2 %. ConclusionsOnline adaptation in MRgRT improved target coverage and OARs sparing at the level of accumulated dose.

Agroforesty Curriculum Management at Tunas Rimba I Kindergarten Purwokerto

This research aims to describe the management of the agroforestry curriculum at Tunas Rimba I Kindergarten, Purwokerto. This research is qualitative. Data was collected using interview, observation, and documentation techniques. The data that has been collected is then analyzed through the data reduction, data presentation, and verification stages. The research results show four activities carried out in the agroforestry curriculum management at Tunas Rimba I Kindergarten, Purwokerto. These four activities include planning the agroforestry curriculum. These planning activities prepared an agroforestry learning schedule and a Daily Learning Implementation Plan (RPPH). Second, organizing the agroforestry curriculum. In this organization, teaching tasks are distributed, the academic calendar is prepared, the curriculum structure is prepared, and the study group is determined. Third, implementing the agroforestry curriculum, where in implementing the curriculum, agroforestry learning activities are held through intracurricular and extracurricular activities so that young children can achieve the agroforestry learning objectives set out in the RPPH. Fourth, an evaluation of the agroforestry curriculum is aimed at determining the success of teachers in implementing the agroforestry curriculum.

THE IMPACT OF COMPETENCE AND EMOTIONAL INTELLIGENCE ON THE PERFORMANCE OF RAUDHATUL ATHFAL TEACHERS IN SIMALUNGUN DISTRICT

Based on the identification of several problems, namely: 1) there are still teachers who are not good at pedagogical competence, such as teachers who are still not good at designing daily learning program planning (RPPH), making learning media, 2) there are still teachers who are not good at emotional intelligence, such as teachers are not good at motivating themselves, that is they are still not good at using their deepest desire to move and guide towards the goals to be achieved, 3) there are still teachers who are not good at preparing lesson plans, implementing learning and evaluating learning which will affect teacher performance. From the identification of the problem, the formulation of the problem can be drawn, namely: 1) Does competence partially affect the performance of Raudhatul Athfal's teachers in Simalungun Regency?; 2) Does emotional intelligence partially affect the performance of teacher Raudhatul Athfal in Simalungun Regency; 3) Does competence and emotional intelligence simultaneously affect the performance of Raudhatul Athfal's teachers in Simalungun Regency? This research is quantitative with the help of the SPSS application. The method used in this study is a survey method with correlational analysis techniques. This study aims to analyze, test, and determine the effect of competency and emotional intelligence variables, partially and simultaneously on the performance of Raudhatul Athfal's teachers in Simalungun Regency. The results of the study show that competence has a partial effect on teacher performance. It can be seen from multiple linear regression analysis through the t-test that the competence variable has a Tcount of 4.893 while Ttable is 1.694 (Tcount 4.893 &amp;gt; Ttable 1.694) with a significant level of 0.000 &amp;lt;0.05, meaning that there is a significant influence between competence on teacher performance. There is a partial influence between Emotional Intelligence with a Tcount of 2.566 while Ttable is 1.694 (Tcount 2.566 &amp;gt; Ttable 1.665) with a significant level of 0.015 &amp;lt;0.05, meaning that there is a positive influence between Emotional Intelligence on teacher performance. There is a positive and simultaneous influence of Competency and Emotional Intelligence variables on Raudhatul Athfal's Teacher Performance in Simalungun Regency. With Fcount of 59.501 with a significant level of 0.000. (Fcount 59.501 &amp;gt; Ftable value 3.29 sig 0.000 &amp;lt;0.05).

Workplace tentativity: biophysical environmental impacts on outdoor work

ABSTRACT Drawing from data gathered for two ethnographic case studies within the U.S. Forest Service, we develop the concept of workplace tentativity to describe the ways that the biophysical environment influences organizational workplace routines. We find that outdoor labor, routines, and plans adjust to biophysical change and uncertainty, and we examine the resulting organizational and micro-interactional dynamics when such instances occur. Under conditions of workplace tentativity, employees frame workplace activities as tentative and subject to change with limited notice, impacting daily work plans, organizationally planned activities, the utilization of materials, and preparation for and response to accidents and injuries. Attention to the impact of the biophysical environment on workplace structures, patterns, practices, and norms is essential in an era of climate crisis.

The Effect of Planned Nursing Care on the Development and Severity of Pressure Ulcers in Elderly Patients: An Interventional Study

Introduction: Pressure ulcer is one of the common problems in hospitals, especially in long-stay inpatient departments and intensive care units. This study was conducted with the aim of investigating the effect of planned nursing care on the occurrence and severity of pressure ulcers in patients admitted to the intensive care units. Methods: In this interventional study, 80 patients were gradually placed in two control and experimental groups. The participants of the experimental group received the care plan based, while the participants of the control group received only the daily and routine care plan. The rate of pressure ulcer development was evaluated based on the scale of the International Pressure Ulcer Society. The data were analyzed using chi-square test and Fisher’s exact test in SPSS version 16 software. Results: The relative and absolute frequency distribution of the research units according to the presence or absence of pressure ulcers after the intervention showed that pressure ulcers in the experimental group decreased significantly (P≤0.05). Also, the difference in the severity of pressure ulcers in the two groups indicated that the intervention reduced the degree, severity, and depth of pressure ulcers. Conclusion: Carrying out planned care in patients who have a high risk of pressure ulcers will reduce the possibility of pressure ulcers, especially with high severity and degree. Therefore, applying the principles of pressure ulcer prevention by the care team is emphasized and recommended for patients who are not able to do this themselves.

EVALUASI PEMBELAJARAN CIPP PADA PEMBELAJARAN STEAM DI PAUD

The CIPP evaluation model is one of the most widely used evaluation methods for conducting assessments, especially in the field of education. This evaluation model is divided into 4 components, namely context evaluation, input, process and results. A formal educational institution needs to continue to carry out a form of evaluation as a form of self-evaluation in order to make the institution better in the future, especially the things that are assessed. The research in this article is about the implementation of the evaluation of the STEAM approach in art centers in PAUD units. The method in this study is qualitative with data collection methods through observation, interviews and documentation. The data analysis technique uses the Huberman and Miles technique which consists of three streams of activities that occur simultaneously, namely data reduction, data presentation, drawing conclusions and verification. The conclusion obtained from the context evaluation is that the STEAM approach to art centers has been carried out well in TK IB 68. Evaluation of inputs to art centers through the STEAM approach is known to have been based on the Daily Learning Implementation Plan (RPPH). The evaluation process is known to be going well by school institutions, this can be seen from the assessment activities carried out at art centers based on the STEAM approach. And the evaluation of the results, namely the evaluation process and the procurement of tools and materials that have been carried out by the teacher can be categorized as going well and adapted to the needs and interests of the child.

Education in extreme ­circumstances: opportunities, ­constraints, risks

The article delves into the issue of the education system’s operation within extreme circumstances, particularly in the context of the COVID-19 pandemic. It underscores the pivotal role of education in mitigating global risks such as environmental, epidemiological, geopolitical, and others. Particular emphasis is given to the realm of distance education during extreme situations, examining its prospects, constraints, and perils.Drawing on research conducted in Ukraine and abroad, notably the nationwide study “High School Student 2021: Daily Practices and Life Plans,” the authors dissect the acquired data across three dimensions: the educational aspect (students’ perspectives on distance learning, shifts in their learning methods due to this educational format, modifications in academic engagement, etc.), technological (availability of devices that can be used to join educational platforms) and competence (skills in using devices, experience in distance learning). The article concludes that online education’s primary benefit lies in its ability to sustain the learning process during extreme circumstances, such as the COVID-19 pandemic and the full-scale Russian invasion of Ukraine. Nevertheless, among the drawbacks of this educational model, the absence of direct interaction among various participants of education is prominently noted. Amid the potential risks, concerns arise about socialization risks and the potential degradation of society’s intellectual capacity due to a potential decline in the quality of educational offerings available to modern youth.

Algorithmic model generation for multi-site multi-period planning of clean processes by P-graphs

Optimal clean process design requires strict constraints to enforce waste and byproduct management, all of which can be formulated in the language of mathematical programming. However, waste management and the utilization of by-products are often carried out in locations or periods other than the production process. The paper describes all modeling steps by P-graphs sufficient to represent raw material availability and production capacities in multiple time periods at multiple sites, as well as transportation and storage capacities of process materials and wastes. These steps are integrated into a single comprehensive model generation algorithm. For easier understanding, each model generation step is illustrated by a case study of planning a multi-site multi-period furniture production process alongside the recent challenges of energy supply and waste management. Finally, the case study of furniture production is analyzed under various circumstances to highlight the power of the proposed tools in daily production and transportation planning. Accordingly, the proposed method provides such alternative 5 best manufacturing and logistics plans that, in the event of a complete failure or overloading of one of the production capacities at either locations, there is still an alternative plan within a 3% profit decrease.

The Influence of Parental Migration on Left-behind Children’s Development in China

Both the number of migrant workers and the number of kids being left behind have substantially increased since the programme was opened up. This study attempts to show how parental migration affects children who are left behind and explore the causes of such negative effects. It turns out that when parents move away, it has a variety of repercussions on the children who are left behind, including their emotional health, academic performance, level of cooperation, and cognitive development. Governments must play a crucial role towards enhancing the living conditions for children who have been left behind in rural areas. This includes providing more opportunities for migrant workers to reunite with their families, providing greater opportunities and time for parents to watch their children, and emphasising relative caring policies in teachers' daily lesson plans. Rural families also have to change their mindset for degrees, and giving more expectations of their children’s learning.

AI dietician: Unveiling the accuracy of ChatGPT's nutritional estimations

We investigate the accuracy and reliability of ChatGPT, an artificial intelligence model developed by OpenAI, in providing nutritional information for dietary planning and weight management. The results have a reasonable level of accuracy, with energy values having the highest level of conformity: 97% of the artificial intelligence values fall within a 40% difference from United States Department of Agriculture data. Additionally, ChatGPT displayed consistency in its provision of nutritional data, as indicated by relatively low coefficient of variation values for each nutrient. The artificial intelligence model also proved efficient in generating a daily meal plan within a specified caloric limit, with all the meals falling within a 30% bound of the United States Department of Agriculture's caloric values. These findings suggest that ChatGPT can provide reasonably accurate and consistent nutritional information. Further research is recommended to assess the model's performance across a broader range of foods and meals.<END ABSTRACT>

Implementation of an early mobility protocol in the neuroscience ICU

Abstract &#x0D; Background: Early mobility is a safe and effective intervention to improve patient outcomes in the neuroscience intensive care unit (ICU). However, mobilization of patients in a neuroscience ICU within an academic medical center was suboptimal, with less than 36% of patients achieving their highest level of mobility.&#x0D; Aim: The purpose of the quality improvement project was to develop and implement a multidisciplinary early mobility protocol, including a safety-screening tool.&#x0D; Methods: Iterative Plan-Do-Study-Act cycles were implemented from April to August 2022. The screening tool assisted nurses in assessing the patient’s eligibility for early mobilization. A mobility section addressing patient-specific mobility screening, barriers to mobility, and a daily mobility plan was added to the provider note templates. Baseline data were collected from September to November 2021; post-implementation data were collected from April to August 2022.&#x0D; Results: There was a reduction in the mean time between admission to the first documented out of bed activity from 3.24 to 2.01 days, p=.061. The mean number of documented out of bed activities significantly increased from 6.13 to 8.35, p = .002. Hospital length of stay significantly decreased from 19.8 to 12.42 days, p=.006.&#x0D; Conclusions: Implementing an early mobility screening tool and protocol in the neuroscience ICU increased mobility for patients with neurological diagnoses. Other hospitals should consider implementing a similar process to help improve patient outcomes.

Empirical analysis of a plan-of-the-day strategy to approximate daily online reoptimization for prostate CBCT-guided adaptive radiotherapy.

Adaptive radiotherapy (ART) can improve the dose delivered to the patient in the presence of anatomic variations. However, the required time, effort, and clinical resources are intensive. This work analyzed a plan-of-the-day (POD) approach on clinical patients treated with online ART to explore implementations that balance dosimetric benefit and clinical resource cost. Eight patients treated to the prostate and proximal seminal vesicles with 26 fractions of CBCT-guided, daily online ART were retrospectively analyzed. With a plan library composed of daily adaptive plans from the initial week of treatment and the original plan, the effect of a POD approach starting the following week was investigated by simulating use of these previously generated plans under 3- and 6-degree-of-freedom patient alignment. The plan selected for each treatment was that from the library that maximized the Dice similarity coefficient of the clinical target volume with that of the current treatment fraction. The resulting distribution of several target coverage and organ-at-risk dose metrics are described relative to those achieved with the daily online reoptimized adaptive technique. The values of target coverage and organ-at-risk dose metrics varied across patients and metrics. The POD schemas closely approximated the reference values from a fully reoptimized adaptive plan yet required less than 20% of the reoptimization effort. The POD schemas also had a much greater effect on target coverage metrics than 6-degree-of-freedom registration did. Organ-at-risk dose metrics also varied considerably across patients but did not exhibit a consistent dependence on the particular schema. POD schemas were able to achieve the vast majority of the dosimetric benefit of daily online ART with a small fraction of the online reoptimization effort. Strategies like this might allow for more practical and strategic implementation of ART so as to benefit a greater number of patients.

The multiobjective traveling salesman–repairman problem with profits: design and implementation of a variable neighborhood descent algorithm for a real scenario

AbstractThis paper introduces a problem that can be seen as a combination of the traveling salesman problem with profits and the traveling repairman problem with profits, coined as the multi‐objective traveling salesman–repairman problem with profits (Mo‐TSRPP). The objective of the Mo‐TSRPP is to simultaneously optimize three objectives: the total cost, total latency, and total profit. Indirectly, the number of nodes visited is also considered although not as an objective itself since it is determined by the size of every efficient solution in the Pareto front. The Mo‐TSRPP emerges as a real‐world problem in which a freelancer, which repairs appliances, wants to plan the daily route. Moreover, the daily plan does not require to visit all customers. To solve the problem, first, a greedy randomized adaptive procedure is designed to generate a set of high‐quality nondominated solutions and then, a variable neighborhood descent algorithm is applied for further improving the initial set. This procedure allows us to attain a good approximation of the Pareto front. To prove the performance of the proposal a comparison is done against three well‐known evolutionary algorithms: NSGA‐II, SPEA‐2, and MOEA/D. Finally, a realistic problem is shown and solved to illustrate the potential of the algorithm.