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Characteristics of two types swapping electric vehicles (EVs) are considered, which include private EVs and electric taxis. Then, a time-space load forecasting method for these swapping EVs is proposed. After that, the forecasting results are taken as the load basis for sizing and locating planning of centralized-battery-charging-stations (CBCSs). In addition, based on the life cycle cost (LCC) theory, a double-layer planning model is established. It takes into account the CBCSs’ planning economy and the optimization for battery logistics system. That is, the planning LCC of CBCSs is conducted by the upper layer optimization. And the lower layer planning optimizes the annual transportation cost of the battery logistics company. The calculation example shows that the proposed planning method for CBCSs is feasible and effective.

In view of the disadvantages of existing planning methods used in CCOS techniques, such as low efficiency and workpieces contain obvious mid-frequency error after polishing, a new tool-path planning method based on improved Prim algorithm was proposed, of which the core idea was consist by following steps: surface data reading, mesh generation, distribution of resident points determining and polishing path generating. After that, comparison of raster path and the path based on improved Prim algorithm was carried out by simulated experiments from aspects of path length and polishing texture. The results indicated that the path based on improved Prim algorithm could shorten path length as well as increase polishing efficiency, moreover, both the texture and mid-frequency errors can be improved by using the path presented. It was concluded that the presented planning method could improve polishing efficiency and machining quality. Then, comparison between raster path and the path based on improved Prim algorithm was carried out by simulated experiments, from two sides of path length and polishing texture. The results indicated that the path based on improved Prim algorithm could shorten path length as well as increase polishing efficiency, moreover, both the texture and mid-frequency errors would be improved by using the presented path. Finally, the validity of presented planning method was proved in machining experiments.

For satisfying the growing demand of parking in urban area and relieving traffic congestion in downtown, under the condition of urban subway park-and-ride (P&R), the methods of site selection and scale calculation of parking lots are studied. Selecting Xi'an Rd. business circle in Dalian as study object, both survey and analysis of parking demand were conducted. Based on the principle of random equilibrium selection, the logit model of P&R demand was constructed. Then the forecasting models of parking demand both in downtown and peripheral zones were proposed respectively. Using the minimum travel distance of vehicles as the objective function, site selection optimization model of P&R station was constructed. The calculation methods of scale for parking lots in both downtown and P&R station were also processed. For the case of Xi'an Rd. business circle, not only the site of P&R station was planned, but the scale of parking berth was calculated. According to the plan and calculation, the total number of parking berth has increased from 3380 to 4011. Among the planned berths, 75.7 % are in the business circle and 24.3 % in P&R stations are outside downtown. Thus, the number of planned berths in the business circle has actually decreased by about 8 %. The research indicates that, for downtown with subway system, by reducing parking berths in downtown and increasing them in P&R stations outside the urban area, this planning method is more beneficial to relieve the problems of parking and traffic congestion in downtown than traditional method.

This paper proposes a multistage distribution network planning (DNP) method that considers multiple planning alternatives, the active management of distributed generation (DG) units and demand response in the context of active distribution networks (ADNs). Representative days are selected for the consideration of uncertainties related with load demand and renewable power generation, during the planning period. The proposed DNP method aims at minimising the net present value of the total investment and operational cost. The proposed DNP considers multiple planning alternatives, such as the reinforcement of existing substations and existing distribution lines, the installation of new distribution lines, and the installation of capacitors. Furthermore, the proposed DNP method incorporates the control capabilities of DG active and reactive power output and demand response schemes. A 24‐bus distribution network and a 144‐bus real world distribution network are used to validate the performance of the proposed method.

Implant placement necessitates an interdisciplinary approach in which a team of dental implant specialists, including an oral surgeon, prosthodontist, periodontist, and oral radiologist, collaborate on the design, execution, and maintenance of the implants to provide the best possible result. According to the data, the vast majority of the participating dentists provide implant-supported restorations to their patients on a regular basis. Surprisingly, the percentage of dentists who plan implant placement and employ backward planning methods was significantly lower. This finding implies that dentists do not always follow the current scientific consensus that the placement of an implant should be based on prosthetic principles.

The article substantiates the need to identify trends in the development of processes demographic in individual countries and regions. The analysis of the determination of demographic processes is a necessary condition for the development of an effective demographic policy. The authors studied the dynamics of the population of the planet as whole, Europe, and Russia over the past 50 years. The assessment of the degree of influence of the measures taken in certain countries of the world on the demographic situation is given. The article deals with both methodological issues of studying the determination of demographic processes, and the results of research based on statistical information. Much attention is paid to the issues of determining the birth rate and mortality. An assessment of the impact of material payments on the birth rate is given. At the same time, the issues of determining migration processes and population aging are not left without attention. To analyze the causes of population migration in the region, the experimental planning method was used. The use of this method allowed us to identify the factors that affect migration processes and to assess the degree of influence of each of them on the level of the migration efficiency coefficient. The study showed the possibility of using the planning method in the study of socio-economic processes. The authors consider three variants of the population forecast of the Russian Federation until 2035, proposed by Rosstat, and assessed possible options for their implementation.

Community Service Activities were carried out in Tegal Alur Village, Kalideres District, West Jakarta. The problem faced by partners is the lack of training that can open up profitable business opportunities for them. The implementation method is carried out starting with a site survey, followed by training and ending with activity analysis. The Lean Canvas planning method is used to get to the heart of the idea, putting all the information on one page, helping to define the main information needed, without unnecessary details. As a result of this training activity, housewives, Family Welfare Development mother (PKK), youth organizations and Micro, Small and Medium Enterprises (UMKM) in Tegal Alur Village, West Jakarta, can start a business by taking action step by step, so that their efforts can generate profits as expected. It can be concluded that this training is beneficial for the community and increases the desire to become entrepreneurs.

The development of new gas and gas condensate fields in a complex external geopolitical environment for the Russian Federation requires the development of methods for selecting the optimal modes for the operation of gas wells. The mathematical apparatus and computational algorithms, which allow, based on accumulated geological and field information, to calculate the long-term dynamics of the flow rates of gas producing wells under the conditions of using potentially possible operating modes are considered. Prediction of long-term dynamics of gas production well rates in practice is necessary for long-term planning of gas production, optimal distribution of productivity between the gas processing unit in the gas gathering network of the enterprise, and the formation of pre-design options for the development of gas deposits. In other words, planning methods based on the accumulated geological and production data of gas well operation modes are needed in order to select from a variety of possible technological modes of operation those that will ensure the optimization of the gas production plan in an unstable economic environment.

Buckwheat can be used in the production of specialized products (including therapeutic and preventive ones) for consumers suffering from gluten intolerance. Buckwheat malt in Russia is not produced on an industrial scale, it is purchased in European countries. It is necessary to know the parameters of processing domestic varieties of buckwheat for the production of buckwheat malt. Mathematical planning methods were used to predict the influence of the main factors of buckwheat germination on the activity of its hydrolytic enzymes for the production of malt with high enzymatic capacity. Dikul buckwheat was studied. Soaking of buckwheat was carried out by air-water method at a temperature of 15-16 °C in tap water to a relative humidity of 46-50 %, air and water pauses were alternated every 4 hours. Germination was carried out for 6 to 7 days at a temperature of 15 to 16 °C until the maximum activity of hydrolytic enzymes of amylolytic and proteolytic action was achieved. The sprouted grain was subjected to fermentation, for which it was left alone for 12-24 hours until the temperature in the middle layer rose to 50-55 °C, stirred and blown with conditioned air with such intensity that the humidity of the malt was 50-52 %, and the temperature in all layers was 67-68 °C for 5 days. Drying was carried out with a gradual increase in temperature from 67-68 °C to 74-75 °C for 16 hours to a humidity of 5-6 %. We predicted how the main factors of buckwheat germination affect the activity of its hydrolytic enzymes. The main factors affecting the activity of enzymes during germination: malting temperature, °C; malting humidity, %; malting duration, day. The criteria for evaluating the influence of the selected parameters were the abilities, units/g of dry substances: amylolytic, saccharifying, and proteolytic. For statistical processing of the study data, central rotatable uniform planning was used, which made it possible to obtain a regression equation that adequately describes the process of buckwheat germination in the course of 20 experiments in 3-fold repetition. To assess the adequacy of the mathematical model, an analysis of variance (ANOVA) of the experiment was performed in the Design Expert program (Stat-EaseInc.). The following values of the output parameters were obtained, units / g of dry substances – amylolytic capacity of 326.7, saccharifying capacity of 40.9 and proteolytic capacity of 381.9 units/g. at the appropriate input: temperature 15 °C; humidity 48 %; duration of malting 6 days.

The article considers the application of methods that make it possible to determine the need for deeper standardization of processes within the framework of the implementation of national programs, based on the influence of the degree of standardization on the time and resource intensity of the implementation of national programs. To determine the impact of the degree of standardization on the implementation time of national programs implementation, it is proposed to use network-planning methods, taking into account the influence of the time required for the development and implementation of additional standards on the implementation of the national program. The impact of standardization on the resource intensity indicators of the implementation of national programs is proposed to be taken into account through the analysis of the dynamics of the amount of finance required for the implementation of the program. For this purpose, it is proposed to use business planning methods, namely: calculation of the costs associated with the development and implementation of additional standards and calculation of the financial benefits from deepening standardization, based on the calculation of the amount of reduction in the cost of financial resources per unit of the result of the national program implementation.

Resource-based cities generally have "high energy consumption, high carbon emissions, and high pollution". Exploring low-carbon planning of resource-based cities means great significance for promoting the low-carbon transformation and development of resource-based cities and achieving "carbon peak" and "carbon neutrality". Based on the two levels of city region and central city, the paper proposes a low-carbon planning method for resource-based cities from four aspects: industrial transformation, land use, road transportation and ecological environment. At the city region level, it is necessary to reasonably determine urban industrial structure and industrial development scale, and meanwhile, optimize the industrial layout by reasonably planning production, living and ecological space and formulating practical space control measures; coordinating the connection between external traffic and traffic system within the city; constructing a carbon sink network composed of green patches-ecological corridors-peripheral matrix. At the central city level, it is necessary to analyze gradient attributes of carbon emissions from different land types, rationally arrange various types of construction land; optimize the layout of urban residence and employment space; increase systematicness of road planning in central urban areas; give full play to the carbon sink role of ecological corridors. Finally, an empirical study is carried out with the case of Xingtai City. The research can provide theoretical basis and path reference for reducing carbon emissions of resource-based cities through spatial planning.

Generalized equivalent uniform dose (gEUD) -based hybrid objective functions are widely used in intensity modulated radiotherapy (IMRT). To improve its efficiency, a novel fuzzy logic guided inverse planning method was developed for the automatic parameters optimization of the gEUD-based radiotherapy optimization. Simple inference rules were formulated according to the knowledge of the treatment planner. Then they automatically and iteratively guide the parameters modification according to the percentage of deviation between the current dose and the prescribed dose. weighting factors and prescribed dose were automatically adjusted by developed fuzzy inference system (FIS). The performance of the FIS was tested on ten prostate cancer cases. Experimental results indicate that proposed automatic method can yield comparable or better plans than manual method. The fuzzy logic guided automatic inverse planning method of parameters optimization can significantly improve the efficiency of the method of manually adjusting parameters, and contributes to the development of fully automated planning.

State policy in the military sphere, defense and military construction is now aimed at creating modern mobile and combat-ready defense forces that will be respected in society and by foreign partners and international organizations, together with other state institutions will ensure comprehensive defense of Ukraine, protection of its sovereignty and territory integrity and inviolability. Numerous scientific publications substantiate various models and the need to increase the effectiveness of defense management in the current environment of managing defense planning processes, especially security, in order to achieve certain strategic goals of defense reform and bring these processes closer to standards adopted in NATO armies. The purpose of the article is to find effective approaches to the formation of a model for managing defense planning processes, bringing them closer to modern needs and the principles and standards adopted in the armies of developed NATO member states. Defense planning is carried out in order to ensure the state's defense capabilities by determining the priorities and directions of development of defense forces, their capabilities, armaments and military equipment, infrastructure, training of troops (forces), as well as developing appropriate concepts, programs and plans taking into account real and potential threats in military sphere and financial and economic capabilities of the state. It is carried out using the capability-based planning method, which aims to develop them in the long term. The defense planning process includes: capability planning; capacity development programming; budgeting and resource management; implementation of programs and plans. In order to qualitatively prepare and implement effective defense management for the management of defense planning processes, it is expedient to improve the methodology of this work in practice, to bring these processes closer to the principles and standards adopted in the armies of NATO member states.

Rural planning plays an important role in rural industrial integration, but there are few researches on the planning methods of rural industrial integration in China at present. Therefore, learning from the successful experience of developed countries and combining with the current situation of rural economic and social development in China is an important means and basic idea to explore the rural planning method of guiding the integration of primary, secondary and tertiary production in rural areas in China.

The article discusses the contributes to the development of a new focus on the use of various mixtures of natural raw materials and waste in the construction materials industry as a strategically important direction for solving the environmental burden and recycling industrial waste with a feasibility study that improves the state of the environment. This problem is particularly relevant in the production of building materials used in environmentally distressed areas of the republic and in conditions of intense corrosion and erosion wear. The production of efficient building materials and products that meet the modern requirements of environmental friendliness, basic physical and mechanical characteristics, availability and cost is an important and not fully solved task in the field of construction and the construction materials industry. Analysis have been conducted on the current state of the local availability of perspective materials for high-quality composite construction materials, their chemical and mineralogical and granulometric properties have been studied, the influence of the granulometric composition of the basic properties of a composite material and features of the structure formation during heat treatment were studies; physical and mechanical properties of the obtained compositions were tested. Optimal compositions and technological schemes for the production of composite materials based on the use of technogenic waste, natural raw materials and their mixtures have been developed to ensure the production of high-quality construction products with specified thermomechanical properties.The optimization of compositions and properties of compositions was carried out using mathematical planning methods, which made it possible to predict changes in the properties of composite materials depending on the number, weight of the components and the size of the filler granules. Experimental batches of at least 3 main types of construction products were obtained.

Centralized methods of planning the use of N devices for the realization of operations on a set of M objects with the scheme of the elementary operation is "one object  k devices" are proposed. Methods include modifications for the following cases: 1) only the described scheme of elementary operation is applied ("rigid" requirement); 2) the named scheme is preferred, but there are possible options of reducing the specified (desired) maximum number k for individual operations ("soft" requirement). Methods suitable for multi-elements dynamic systems in real time of their operation. Under planning conditions, the device system and the set of objects are multi-element. Planning methods belong to the category of "fast" methods, which suitable for dynamic multi-element systems in real time of their operation. The verification of the methods is implemented for the generalized system and for the particular case of the satellite system of observation of orbital objects.

Nowadays, the daily forecast for employee losses becomes a major issue. Staff participation is an important issue for the organization, especially when professional technical staff and key people in the organization come from good positions. This leads to a loss of finances to replace skilled labor. Therefore, we use data from current and former employees to analyze common causes of employee access or influence. To avoid employment, we use several planning methods, namely: Decision Tree, Log-log of Backlog, SVM, KNN, Random Forest, Bayes Naive. To do this, we use the method to select employment information and analyze the results to avoid employee income. Companies need to anticipate employee incentives and contribute to economic growth by reducing manpower.

One cycle of chemotherapy does not eliminate all cancer cells, therefore it takes a repeated cycle (Williams, et al, 2016), so the guarantee the availability of chemotherapy drugs is needed. An effective drug requirement planning is required to ensure the availability of chemotherapy drug. This study was intended to determine the effectiveness of planning the need for chemotherapy drugs using the morbidity method on the availability of chemotherapy drugs in Dr. Ramelan Navy Hospital. This study was an observational study with a cross sectional study design. The instrument used in this study was the data collection sheet with data sources prescription sheets and sheets of chemotherapy drug reconstitution during 2015-2017. Descriptive data analysis and to determine effective planning methods using indicators of drug availability. The results showed that the planning of drug needs with the morbidity method can better guarantee the availability of chemotherapy drugs and can minimize drug shortages compared to the consumption method that has been done so far in Dr. Ramelan Navy Hosptal. So it can be concluded that in this study, the morbidity method is effective in meeting the needs of chemotherapy drugs.

The development of an integrated energy system (IES) is conducive to promoting the transformation of the energy system and helping to achieve the ‘double carbon’ goal in China. The IES integrates cooling, heating, electricity, gas, and other energy resources, which is significantly more difficult than single energy network planning. This paper systematically sorts out the process of IES network planning and proposes an improved methodology. Firstly, the bottom-up dynamic multiple-load forecasting method of 8760 h a year is proposed as the basis of system configuration and capacity selection. Subsequently, a planning method for energy station location and route optimization using the Dijkstra algorithm is constructed by applying the P-median optimization model. Finally, when optimizing the capacity allocation of the IES, the complementary characteristics of natural gas, electricity and heat, as well as the corresponding energy demand characteristic, have been fully considered, so that the optimization objectives can be reasonably determined. Through the actual calculation, it is found that the optimization method proposed in this paper can reduce the construction cost of the network by 41%. The work combines the process of energy network planning and capacity configuration of IES, which provides a simple, easy and economical solution for IES planning in new areas.

In the Armed Forces of Ukraine, work continues to improve the efficiency of defense planning and management of defense resources. The algorithm of defense planning for the development of the Armed Forces of Ukraine, step by step, uses the results of the analysis of the experience of the leading countries of the world, which have moved from defense planning based on threats to defense planning, focused on the acquisition by troops (forces) of the capabilities necessary to fulfill the tasks assigned to them. The list of tasks of the Armed Forces of Ukraine is determined on the basis of probable scenarios of their use. One of the key points in the effective planning of the use of the Armed Forces according to the corresponding scenario is a real and reasonable determination of the amount of necessary defense resources (human, logistical, financial). At the present stage of transformation of the defense planning system to NATO standards, as well as the application of the planning method based on capabilities in the General Staff of the Armed Forces of Ukraine, it is necessary to improve the existing methodological approaches to determine the needs for defense resources for the use of the Armed Forces of Ukraine according to certain scenarios of their use. Also, an urgent task today is the need to assess the sufficiency of the real economic and temporary capabilities of the state to ensure the use of the Armed Forces for the scenarios of their use determined by it. The general algorithm for assessing the cost of defense resources for the use of the Armed Forces of Ukraine in conflicts of varying intensity should take into account the economic realities of the development of the country's national economy. In the article, the authors proposed their views on improving the existing approaches to calculating the amount of necessary defense resources, the procedure and content of assessing their cost according to the corresponding scenarios for the use of the Armed Forces in order to further assess the economic capabilities of the state to provide them. The main results of the article are the procedure for assessing the cost of fulfilling the tasks assigned to the Armed Forces of Ukraine and the cost of conducting hostilities of varying intensity, as well as the general algorithm for making calculations.

This paper presents a phase planning method specially designed for coal deposits with nearly horizontal, bedded coal seams. The geology of this type of deposit is modeled into a column model, instead of a block model, to avoid coal-rock mixing in blocks. A nested pit generation algorithm is developed for producing a series of nested, least-strip ratio pits with a column model as its input. The algorithm completely overcomes the troublesome gap problem. Taking the least-strip ratio pits as possible phase states, a dynamic programming formulation is proposed to simultaneously optimize the number of phases, the phase-pits, and the ultimate pit, with an objective of maximizing the net present value. The merits and capability of the proposed method are demonstrated through a case study on a large coal deposit.

Maila Sari Brebes Nugget Company is one of the companies engaged in the food industry, in that its sales of Nugget products have a fluctuating volume of sales each month due to the lack of application of scientific forecasting planning methods, so forecasting techniques need to be applied by the company. This study aims to optimize the sales plan of Maila Sari Brebes Nugget, do the calculation between the Exponential Smoothing method and the Least Square method of the error value, can be used as an appropriate and effective method in accordance with the real sales data of Maila Sari Brebes. Using the Microsoft Excel 2010 application and POM-QM for Windows 5. Based on the results of the analysis that has been done that the Exponential Smoothing method α = 0.9 has a smaller difference with an average difference of 508.892833 and an average forecast error rate of 3.44% per month, compared to the Least Square method which has an average difference of 6064,772 and an average error rate of forecasters of 41.67% per month

The paper investigates modern trends in the development of innovative systems in Russia. These trends are caused, on the one hand, by the lack of a clearly formulated concept of an innovation system, and, consequently, by the inability to determine the ways of its development, and by the active use of undeservedly forgotten program-target planning methods, on the other hand. A detailed analysis of various positions and statistical materials allowed us to prove that, contrary to the generally accepted opinion, the Russian model of public administration and financing of innovative activities has signs of cluster and state-corporate types. The article considers the existing approaches to the management of innovation and investment activities of organizations, which is aimed directly at reproduction processes, in particular, the reproduction of fixed capital. The authors substantiate the necessity of creating territorially grouped innovation systems, which is explained by the dependence of industries and sectors of the economy on each other on the technological principle and the need to create technological links between them to realize their potential advantages within the framework of the implementation and creation of innovative products.

Vigorously developing new energy is an important measure to deal with the energy crisis and environmental degradation, but the volatility and randomness of its output have brought great challenges to the new energy consumption. In this paper, the maximum new energy consumption is taken as the objective function, and the power flow constraints, multi-energy source capacity constraints and electrical constraints are taken as the constraints. Based on the complex adaptive system theory, the minimum construction step size of new energy sources is taken as the agent for modeling, focusing on the coordination among multiple sources, adjusting the installed node position and capacities of various types of power sources to obtain the optimal layout of power sources for multi-energy power systems. Based on the actual meteorological and operational data of a regional power grid in Northwest China, the original power system is re-planned. The simulation results verify the effectiveness of the proposed planning method.

This article presents demand response techniques for the participation of datacenters in smart electricity markets under the smart grid paradigm. The proposed approach includes a datacenter model based on empirical information to determine the power consumption of CPU-intensive and memory-intensive tasks. A negotiation approach between the datacenter and clients and a heuristic planning method for energy reduction optimization are proposed. The experimental evaluation is performed over realistic problem instances modeling different types of clients. Results indicate that the proposed approach is effective to provide appropriate demand response actions according to monetary incentives.

Background The aim of the study was to develop and assess a technique for the optimization of breast electronic tissue compensation (ECOMP) treatment plans based on the breast radius and separation. Materials and methods Ten ECOMP plans for 10 breast cancer patients delivered at our institute were collected for this work. Pre-treatment CT-simulation images were anonymized and input to a framework for estimation of the breast radius and separation for each axial slice. Optimal treatment fluence was estimated based on the breast radius and separation, and a total beam fluence map for both medial and lateral fields was generated. These maps were then imported into the Eclipse Treatment Planning System and used to calculate a dose distribution. The distribution was compared to the original treatment hand-optimized by a medical dosimetrist. An additional comparison was performed by generating plans assuming a single tissue penetration depth determined by averaging the breast radius and separation over the entire treatment volume. Comparisons between treatment plans used the dose homogeneity index (HI; lower number is better). Results HI was non-inferior between our algorithm (HI = 12.6) and the dosimetrist plans (HI = 9.9) (p-value > 0.05), and was superior than plans obtained using a single penetration depth (HI = 17.0) (p-value < 0.05) averaged over the 10 collected plans. Our semi-supervised algorithm takes approximately 20 seconds for treatment plan generation and runs with minimal user input, which compares favorably with the dosimetrist plans that can take up to 30 minutes of attention for full optimization. Conclusions This work indicates the potential clinical utility of a technique for the optimization of ECOMP breast treatments.

Latest standards for transmission system planning require investigation of the performance during the simulta neous loss of two elements and an assessment of the risk of cascading outages. Consequently, transmission system expansion must also be supported by in-depth security analyses. In this study, we propose a risk-informed transmission expansion planning method. At the core of the method is an AC based cascading failure model that simulates the power system responses after contingencies. The method aims to provide an optimal expansion plan striking the balance between the cost of expansion and the risk of systemic failures. Addressing this chal lenge requires a simulation based multi-objective optimization, which we tackle using a meta-heuristic algo rithm. The tool developed for transmission expansion planning is applied to the IEEE 118-bus system and compared with state-of-the-art transmission expansion approaches. Remarkably, the proposed TEP procedure produces solutions that improve system security at comparable expansion costs., Electric Power Systems Research, 204, ISSN:0378-7796, ISSN:1873-2046

Critical interference error can be mostly resulted from illogical tool-path generations in the penetration and retraction segments of internal cylindrical thread helical milling. Therefore, a less interference tool-path planning method is proposed for the quarter revolution penetration and retraction trajectories in internal cylindrical thread helical milling. Firstly, the parametric expression of the complete tool path of internal cylindrical thread helical milling is established; after that, a definition of eccentricity parameter m is given to adjust the radius of the penetration and retraction trajectories, and Z-axis coordinate of any point on the tool path is defined as a function of the θ; thus, the planned penetration and retraction trajectories in internal cylindrical thread helical milling with the m are derived; finally, the proper eccentricity parameter m is decided to improve the machining accuracy of thread by exploring the influence of the m on the interference error. Taking the experimental of milling, an M20 × 1.5 thread using a φ8 × 1.5 cutter as one of the examples that indicate the maximum interference error of the planning method (m = 0.4) can be reduced by 30.93%, compared with the original trajectory, and can dramatically improve the precision of internal cylindrical thread helical milling.

Despite the large amount of research devoted to economic uncertainty, enterprises are still held hostage by unforeseen circumstances. This is facilitated by management focused on forecasting average revenue values, while the most serious consequences are caused by random fluctuations in sales. The focus of this study is a mathematical model of revenue under conditions of uncertainty in demand, which can be used to develop planning methods based on separation, deterministic and random components of sales.

Purpose To propose a method of optimizing intensity modulated proton therapy (IMPT) plans robust against dosimetric degradation caused by random anatomic variations during treatment. Methods and Materials Fifteen patients with prostate cancer treated with IMPT to the pelvic targets were nonrandomly selected. On the repeated quality assurance computed tomography (QACTs) for some patients, bowel density changes were observed and caused dose degradation because the treated plans were not robustly optimized (non-RO). To mitigate this effect, we developed a robust planning method based on 3 CT images, including the native planning CT and its 2 copies, with the bowel structures being assigned to air and tissue, respectively. The RO settings included 5 mm setup uncertainty and 3.5% range uncertainty on 3 CTs. This method is called pseudomultiple-CT RO (pMCT-RO). Plans were also generated using RO on the native CT only, with the same setup and range uncertainties. This method is referred to as single-CT RO (SCT-RO). Doses on the QACTs and the nominal planning CT were compared for the 3 planning methods. Results All 3 plan methods provided sufficient clinical target volumes D95% and V95% on the QACTs. For pMCT-RO plans, the normal tissue Dmax on QACTs of all patients was at maximum 109.1%, compared with 144.4% and 116.9% for non-RO and SCT-RO plans, respectively. On the nominal plans, the rectum and bladder doses were similar among all 3 plans; however, the volume of normal tissue (excluding the rectum and bladder) receiving the prescription dose or higher is substantially reduced in either pMCT-RO plans or SCT-RO plans, compared with the non-RO plans. Conclusions We developed a robust optimization method to further mitigate undesired dose heterogeneity caused by random anatomic changes in pelvic IMPT treatment. This method does not require additional patient CT scans. The pMCT-RO planning method has been implemented clinically since 2017 in our center.