Individual Operations Research Articles

A Comparison of Several Linear Genetic Programming Techniques

A comparison between four Genetic Programming techniques is presented in this paper. The compared methods are Multi-Expression Programming, Gene Expression Programming, Grammatical Evolution, and Linear Genetic Programming. The comparison includes all aspects of the considered evolutionary algorithms: individual representation, fitness assignment, genetic operators, and evolutionary scheme. Several numerical experiments using five benchmarking problems are carried out. Two test problems are taken from PROBEN1 and contain real-world data. The results reveal that Multi-Expression Programming has the best overall behavior for the considered test problems, closely followed by Linear Genetic Programming.

Outcomes of 584 cattle caesarean sections performed in a UK first opinion practice.

This retrospective cohort study evaluated 584 cattle caesarean sections (C-sections) performed at a first opinion practice in Southwest England between 2015 and 2021. Outcomes were recorded contemporaneously, and procedures were followed up after 14 days. Thirty-one dams died within 14 days of undergoing a C-section (94.7% survival rate). Dam parity and purpose did not significantly impact mortality. Dams were at 2.7 times greater odds of dying within 14 days if they delivered a stillborn calf (p < 0.05, 95% confidence interval [CI] = 1.20‒6.13), and at 2.9 times greater odds of dying within 14 days if they were recumbent for some, or all, of the C-section (p < 0.05, 95% CI = 1.02‒8.2). Among the 428 procedures where calf outcomes were recorded, 32.9% (n = 141) were stillborn, reflecting previous studies reporting perinatal mortality. Uterine torsion was anecdotally listed as the reason for operating in 34 cases, and 58.1% (n = 18) of these C-sections resulted in a dead calf. Despite the large number of cases studied, all C-sections were carried out by a single veterinary practice. Individual operator(s) and farms were not recorded and could be undetected confounding variables. This study's results provide much needed relevant benchmarking for completing in-house practice audit cycles, ensuring improved clinical governance and outcomes.

Side-by-Side Economic Process Model for the Comparison and Evaluation of Magnetic Bead-Based Processes and Legacy Process for the Manufacturing of Monoclonal Antibodies

This study models two alternative downstream processes based on magnetic separation with the objective of understanding the economic feasibility of these processes compared to the traditional mAb process. The key focus lies in the economic understanding of the cell harvest and capture steps in the models. Here, the models revealed that integrating cell removal and product capture in a single operation is the main factor driving the unified productivity between USP and the magnetic bead-based processes. This results in significant economic benefits, such as savings in both the cost of goods per gram of mAb and fixed costs, as well as increasing annual facility output. The predicted savings potential approaches 38% for COGs, 17% for capital investment, and 40% for annual facility output. For mammalian cell-based manufacturing, the magnetic separation-based DSP provides a highly valuable option due to its integration of several individual unit operations compared to the traditional process both in reducing process time and cost and accommodating higher demands.

Abstract 4136704: Comparison of Early Clinical Outcomes with Balloon-Expanding Valves Versus Self-Expanding Valves in Transcatheter Aortic Valve Replacement: A Meta-Analysis of Randomized Controlled Trials

Background: Transcatheter aortic valve replacement (TAVR) is an effective percutaneous intervention in patients with severe aortic stenosis, particularly in those with contraindications for surgical repair. Currently, two types of aortic valves are used in clinical practice: balloon-expanding valves (BEV) and self-expanding valves (SEV). The current data comparing early (30-day) clinical outcomes of BEV to SEV in patients with severe aortic stenosis undergoing TAVR are inconsistent. Methods: A systematic literature search spanning PubMed, Embase, Cochrane, and Scopus databases was conducted to retrieve randomized controlled trials (RCTs) comparing balloon-expanding valves to self-expanding valves in patients undergoing TAVR. The DerSimonian and Laird random-effects model was used to pool the odds ratios (OR) with 95% confidence intervals. Statistical significance was set at p&lt;0.05. Results: This meta-analysis included five RCTs with 2190 severe aortic stenosis patients (1097 in the BEV group and 3621 in the SEV group). BEV-TAVR was associated with a significantly lower risk of 30-day new permanent pacemaker (PPM) implantation [OR: 0.67; 95% CI: 0.48, 0.93; p=0.02] and 30-day re-hospitalization for heart failure [OR: 0.20; 95% CI: 0.04, 0.96; p=0.04] compared to SEV-TAVR. The risks of 30-day mortality, 30-day cardiac mortality, 30-day all-cause stroke, 30-day myocardial infarction, 30-day life-threatening bleeding, 30-day vascular complications, 30-day acute kidney injury, and 30-day repeat procedures for valve-related dysfunction were comparable between the two groups. Conclusion: TAVR in patients with severe aortic stenosis using BEV is advantageous over SEV in terms of 30-day new PPM implantation and 30-day rehospitalization for heart failure, with comparable risks for other outcomes. These findings underscore the safety and efficacy of newer generation valves, including Sapien 3 and EvolutPro, in TAVR. The choice of prosthetic aortic valve is dependent on individual anatomy and operator preference. Further RCTs are warranted to evaluate other newer-generation valves with varying severities of aortic stenosis.

A Discrete Brain Storm Optimization Algorithm for Hybrid Flowshop Scheduling Problems with Batch Production at Last Stage in the Steelmaking-Refining-Continuous Casting Process.

The iron and steel industry is energy-intensive due to the large volume of steel produced and its high-temperature and high-weight characteristics, sensors such as high-temperature application sensors can be utilized to collect production data and support the process control and optimization. Steelmaking-refining-continuous casting (SRCC) is a bottleneck in the iron and steel production process. SRCC scheduling problems are worldwide problems and NP-hard. The problems are not only important for iron and steel enterprises to enhance production efficiency, but also play a significant role in saving energy and reducing resource consumption. SRCC scheduling problems can be modeled as hybrid flowshop scheduling problems with batch production at the last stage. In this paper, a Discrete Brain Storm Optimization (DBSO) algorithm is proposed to handle SRCC scheduling problems. In the proposed DBSO, population initialization and cluster center replacement are specially designed to enhance the intensification abilities. Moreover, a perturbation operator is devised to enhance its diversification abilities. Furthermore, a new individual generation operator is devised to improve the intensification and diversification abilities simultaneously. Experimental results have demonstrated that the proposed DBSO is an efficient method for solving SRCC scheduling problems.

Data-Driven Clustering Analysis for Representative Electric Vehicle Charging Profile in South Korea.

As the penetration of electric vehicles (EVs) increases, an understanding of EV operation characteristics becomes crucial in various aspects, e.g., grid stability and battery degradation. This can be achieved through analyzing large amounts of EV operation data; however, the variability in EV data according to the user complicates unified data analysis and identification of representative patterns. In this research, a framework that captures EV charging characteristics in terms of charge-discharge area is proposed using actual field data. In order to illustrate EV operation characteristics in a unified format, an individual EV operation profile is modeled by the probability distribution of the charging start and end states of charge (SoCs).Then, hierarchical clustering analysis is employed to derive representative charging profiles. Using large amounts of real-world, vehicle-specific EV data in South Korea, the analysis results reveal that EV charging characteristics in terms of the battery charge-discharge area can be summarized into seven representative profiles.

Sustainability and Efficiency in the Implementation of Technical Infrastructure Projects in an Urban Environment

The individual national programs through which part of the common policies of the EU are implemented contain strict requirements regarding the scope of measures financed by means of funds from the Union budget. In general, the programs are structured in such a way as to ensure both demarcation and complementarity between them, in order to achieve a certain degree of synergism accompanied by long-term investment. There are some opportunities to increase sustainability and efficiency in the implementation of technical infrastructure projects in urban environments financed by EU funds. The same are revealed when analyzing the scope of the specific measures implemented by different beneficiaries. They arise mainly from technological features, incl. consistency in the implementation of individual construction operations. The present study focuses on such possibilities, incl. specific actions contributing to increasing the efficiency of investments and saving public funds in the conditions of their limited amount. Two specific programs are covered, the implementation of which is forthcoming within the 2021-2027 programming period.

МҰНАЙ ЖӘНЕ ГАЗ КЕНОРЫНДАРЫНЫҢ ӨНІМДЕРІН ӨНДІРУДЕ ҚАЗІРГІ ЗАМАНҒЫ ЦИФРЛЫ ЖӘНЕ ЗИЯТКЕРЛІ ТЕХНОЛОГИЯЛАРДЫ ҚОЛДАНУ АСПЕКТІЛЕРІ

Most oil fields cover thousands of square kilometers, and some have reserves in difficult local conditions (heat, permafrost, desert, deep water) or difficult to recover. Due to these factors and a number of other problems related to technological safety, there are difficulties in the development of oil fields (with a steady increase in demand for oil and gas). Therefore, oil companies still need a highly reliable digital infrastructure that provides high productivity and security and manages many of the devices used in the oil and gas business throughout the field. Therefore, in recent years, oil companies around the world are increasingly managing their oil fields using "smart" technologies. They have proven to be a powerful tool for ensuring the safety of oil fields and increasing labor productivity, as well as economic efficiency. The technologies used include the improvement of all stages of the work process through the rapid acquisition of production data associated with advanced analytics, which contributes to a more complete and efficient development of the oil field. With experience in the implementation of "intelligent" technologies, it already shows high efficiency and very reliable results (both in terms of the oil production process itself and in terms of reducing the cost of individual operations). The use of modern digital and intelligent technologies in the production process in the oil and gas sector plays an important role in order to increase efficiency, ensure safety and reduce environmental impact. Application of digital technologies-data collection and analysis: IoT sensors (Internet of Things) allow you to collect data from deposits in real time and send it to analytical platforms. Field modeling: Using digital Twin technology, virtual field models are created that allow you to predict and optimize production processes. Automation: The automated systems and robotics used help to increase productivity in the management of the oil and gas production process.

Assessing the spatial variability of cage movement and velocity attenuation of an off-bottom oyster farm and its influence on eastern oyster (Crassostrea virginica) growth performance

The global shellfish aquaculture industry has expanded over the last seven decades. Similarly, the size of individual shellfish farming operations has grown in some states. Circulation processes in natural water bodies are dynamic and vary across multiple temporal and spatial scales. How gear installation affects the circulation of currents and waves, and subsequent phytoplankton delivery to crops within farms, is largely unknown. Documenting and understanding variability in wave and current energy within an individual farm could help optimize production. Our study sought to understand the variability in oyster growth attributable to hydrodynamic and atmospheric forcing across an active commercial shellfish aquaculture lease in the Patuxent River, Maryland. We observed a 17 % reduction in water flow downstream of the farm (rho = −0.673, p = 0.002, Spearman rank test), suggesting the bottom cages attenuated downstream current velocity during flood tides. Differences in flow speed and the movement of cages and oysters throughout the farm correlated with variances in oyster shell morphology and oyster survival while in bottom cages. Our results demonstrate the occurrence of variability in production within an individual farm location. Further, our findings suggest that insight into the spatial growth patterns across a lease can be practical for forecasting growth and quality of cultured oysters and may enable growers to strategically place oysters within their farm to improve yield and product consistency.

A-331 Monitoring Operators Proficiency at Point of Care is Crucial for Reliable Patient Values. A Practical Example with Patient Blood Chloride, Potassium and Sodium Measurands Assayed with i-STAT®

Abstract Background While i-STAT® cartridges offer the Physician a spectrum of analytical methods at the point of care for prompt diagnosis and interventions, these methods have to be harmonized with the laboratory methods in order to reliably detect shifts and trends. With this practical example we illustrate the importance of a program of routine comparisons between the i-STAT® and laboratory methods to detect analytical differences exceeding the CLIA’s criterion and potentially having adverse clinical implications. Methods Patient blood chloride (Cl), potassium (K) and sodium (Na) values as obtained by nurses with i-STAT Chem 8 ™ cartridges (Abbott Laboratories) at the point of care, where daily compared with the values as obtained with the Laboratory method (two cobas 6000®, Roche Diagnostics) using green top BD® lithium heparin tubes (Becton Dickinson) collected within thirty minutes of the i-STAT assay. The data were electronically stored in RALS™ (RALS Informatics) and transferred to Minitab® (Version 21, Minitab Inc.) statistical software. The two analytical methods were compared using the orthogonal and the polynomial ordinary least squares (POLS) regression models and their graphic representations. The aptness of the methods was evaluated with the standardized residuals diagnostics for normality, independence, outliers (Standardized residual &amp;gt;|3|) and influential observations (Hi&amp;gt;0.5). For acceptance of the differences the CLIA’s total error criterion was employed. (CI: target value ± 5%; K: target value ± 0.5 mmol/L; Na: target value ± 4 mmol/L). Results In the first four months of the study the number of differences exceeding the CLIA’s criterion was not acceptable. [Cl: 10% (165/1564); K: 7% (109/1593); Na: 4% (66/1586)]. These differences were occurring throughout the analytical range (AMR). Consequently, the operator’s technique was suspected and the POCT senior technologists (CA, FA) adopted operator specific interventions. This strategy was effective in the following month and the improvements were maintained for seven consecutive months. Monthly differences exceeding the CLIA’s criterion decreased significantly [Cl:1.9% (52/2777): K:0.9% (25/2868): Na:0.5% (15/2896)]. This was clearly illustrated with the dot plot by date and the parallel box plots by month. Regression analysis showed that the orthogonal and the OLS models were equivalent. Cl: Orthogonal y=1.7+0.99x, OLS y=12+0.88x. K; Orthogonal y=0.2+1.2x, OLS y=0.1+0.96x. Na: orthogonal y=3+0.98x, OLS y=14+0.9x. Additionally, the POLS model showed a linear relationship within the AMR intervals with few outliers (Cl=11; K=7; Na=9), no influential observations (Hi&amp;lt;0.5) and equality of monthly regression lines (P&amp;gt;0.05). Conclusions The implementation of daily comparisons between patient values as obtained with the i-STAT method and those as obtained by the Laboratory method in the interval of thirty minutes, allowed the identification of individual operators requiring additional training. This strategy ensured reliable performance for eight consecutive months. This study clearly showed that the addition of continuous supervision and training of operators to quality control and quality assurance practices, ensured the interchangeability of patient values as obtained with i-STAT and those as obtained with the Laboratory method. Electronic collection of data and analysis with appropriate statistical software, such as Minitab, was crucial for the implementation of this program.

IDE-SVM algorithm and it's usage in physical layer security method for IoT

To address the problem that there is no standard for the parameter selection of support vector machine (SVM) algorithm, a parameter optimization selection method based on the integrated improved differential evolution (IDE) algorithm is proposed, which uses the minimization of the classification error rate as the optimization criterion and the improved differential evolution algorithm to optimize the combination of SVM parameters to obtain an SVM algorithm with higher classification accuracy. At the same time, to avoid the basic DE algorithm from falling into local optimum when solving the SVM parameter selection problem and to improve the search efficiency of the DE algorithm. In this paper, an improved differential evolutionary algorithm is proposed to obtain a DE algorithm with faster convergence and higher accuracy by using the circular arc function for adaptive control of the variance scaling factor F and the crossover probability factor R, combining with the random newborn individual replacement operation. Based on this, an IDE-SVM IoT physical layer security method based on IDE-SVM is proposed. The experimental results show that the authentication accuracy of the physical layer security method based on the improved SVM algorithm is higher than others.

SQL2FPGA: Automated Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms

Today’s big data query engines are constantly under pressure to keep up with the rapidly increasing demand for faster processing of more complex workloads. In the past few years, FPGA-based database acceleration efforts have demonstrated promising performance improvement with good energy efficiency. However, few studies target the programming and design automation support to leverage the FPGA accelerator benefits in query processing. Most of them rely on the SQL query plan generated by CPU query engines and manually map the query plan onto the FPGA accelerators, which is tedious and error-prone. Moreover, such CPU-oriented query plans do not consider the utilization of FPGA accelerators and could lose more optimization opportunities. In this article, we present SQL2FPGA, an FPGA accelerator-aware compiler to automatically map SQL queries onto the heterogeneous CPU-FPGA platforms. Our SQL2FPGA front-end takes an optimized logical plan of an SQL query from a database query engine and transforms it into a unified operator-level intermediate representation. To generate an optimized FPGA-aware physical plan, SQL2FPGA implements a set of compiler optimization passes to (1) improve operator acceleration coverage by the FPGA, (2) eliminate redundant computation during physical execution, and (3) minimize data transfer overhead between operators on the CPU and FPGA. Furthermore, it also leverages machine learning techniques to predict and identify the optimal platform, either CPU or FPGA, for the physical execution of individual query operations. Finally, SQL2FPGA generates the associated query acceleration code for heterogeneous CPU-FPGA system deployment. Compared to the widely used Apache Spark SQL framework running on the CPU, SQL2FPGA—using two AMD/Xilinx HBM-based Alveo U280 FPGA boards and Ver.2020 AMD/Xilinx FPGA overlay designs—achieves an average performance speedup of 10.1x and 13.9x across all 22 TPC-H benchmark queries in a scale factor of 1 GB (SF1) and 30 GB (SF30), respectively. While evaluated on AMD/Xilinx Alveo U50 FPGA boards, SQL2FPGA using Ver. 2022 AMD/Xilinx FPGA overlay designs also achieve an average speedup of 9.6x at SF1 scale factor.

The Integration of Advanced Mechatronic Systems into Industry 4.0 for Smart Manufacturing

In recent years, the rapid advancement of digital technologies has driven a profound transformation in both individual lives and business operations. The integration of Industry 4.0 with advanced mechatronic systems is at the forefront of this digital transformation, reshaping the landscape of smart manufacturing. This article explores the convergence of digital technologies and physical systems, with a focus on the critical role of mechatronics in enabling this transformation. Using technologies such as advanced robotics, the Internet of Things (IoT), artificial intelligence (AI), and big data analytics, industries are developing intelligent and interconnected systems capable of real-time data exchange, distributed decision making, and automation. The paper further explores two case studies: one on a smart plastic injection moulding machine and another on soft robots. These examples illustrate the synergies, benefits, challenges, and future potential of integrating mechatronics with Industry 4.0 technologies. Ultimately, this convergence fosters the development of smart factories and products, enhancing manufacturing efficiency, adaptability, and productivity, while also contributing to sustainability by reducing waste, optimising resource usage, and lowering the environmental impact of industrial production. This marks a significant shift in industrial production towards more sustainable practices.

PSXII-14 Fecal near infrared reflectance spectroscopy for indirect prediction of methane emissions from grazing cattle

Abstract Methane (CH4) production from enteric fermentation of ruminants accounts for over a quarter of the greenhouse gas emissions from the agriculture sector in the U.S. Accurate and precise quantification of CH4 is essential to identify strategies for mitigating CH4 emissions. Numerous techniques and methodologies exist for measuring enteric CH4 emissions from ruminants, however, many were designed for specific research purposes, potentially limiting their applicability on commercial farms. Our objective was to evaluate the application of fecal near infrared reflectance spectroscopy (FNIRS) to provide inputs for indirect CH4 prediction calibrations. The Grazingland Animal Nutrition Laboratory (GAN Lab) has produced FNIRS predictions of grazing livestock diet quality since 1995 in conjunction with animal performance (weight/body condition change) generated by the Nutritional Balance Analyzer (Nutbal) Software package. FNIRS is a non-invasive approach that provides a significant opportunity to inform models for grazing cattle CH4 emissions. From a comprehensive U.S. dataset of approximately 30,000 samples, we selected a subset representing beef cattle grazing the gulf coast region of Texas from 2016 to 2019 (n = 85). Inputs of diet crude protein (CP), diet digestible organic matter (DOM), live weight (LW), and estimated live weight change (LWC) were used to predict feed intake (FI) employing a published equation and, from outputs generated by Nutbal, i.e. FI_Eq and FI_Nut, respectively. The FI (kg DM/animal.day) generated by both methods were applied to established prediction equations to generate preliminary estimates of CH4 emissions (CH4 FI_Eq and CH4 FI_Nut, respectively). Differences among estimations were assessed through ANOVA, with significance determined at P &amp;lt; 0.05. The estimated FI was different (P &amp;lt; 0.01) for both methodologies, resulting in different (P &amp;lt; 0.01) predictions of CH4 emissions. The CH4 prediction for CH4 FI_Eq was 0.24 ± 0.03 kg/animal.day, compared to 0.38± 0.06 kg/animal.day for CH4_Nut. A difference was observed between years for the CH4 predictions estimated with CH4 FI_Eq (P &amp;lt; 0.01). The FNIRS/Nutbal technique provided useful inputs to the established CH4 calibrations but will need to be validated against CH4 reference methods. The Gan Lab FNIRS/Nutbal dataset offers an opportunity to not only estimate U.S. grazing ruminant CH4 emissions over the past 30 years, but also predictions of current and future emissions at individual operation to national scales. This technique will enable producers with the knowledge to optimize forage resources management, mitigate CH4 emissions, and enhance the sustainability of grazing animal agriculture.

Design of a 240 elements antenna system for 5G massive MIMO applications with an inclined beam and two operating modes

A massive MIMO (multiple-input-multiple-output) antenna system for 5G base stations is developed, featuring 240 elements and 60 ports. The system supports two modes: individual port operation and network operation. It has a rectangular shape with dimensions of 28×16.8×0.32 cm³ and consists of three layers per side, with 15 ports per layer. Each port contains a 2×2 patch sub-array operating at 3.5 GHz, with beam tilting to generate uncorrelated radiation patterns. The system provides a measured bandwidth of 252 MHz, covering the 3.39–3.64 GHz band. Gain and envelope correlation coefficients are evaluated according to mMIMO parameters. A prototype is fabricated, and the results obtained through CST simulations are validated by experimental measurements.

Flat-top plasma operational space of the STEP power plant

Abstract STEP is a spherical tokamak prototype power plant that is being designed to demonstrate net electric power. The design phase involves the exploitation of plasma models to optimise fusion performance subject to satisfying various physics and engineering constraints. A modelling workflow, including integrated core plasma modelling, MHD stability analysis, SOL and pedestal modelling, coil set and free boundary equilibrium solvers, and whole plant design, has been developed to specify the design parameters and to develop viable scenarios. The integrated core plasma model JETTO is used to develop individual flat-top operating points that satisfy imposed criteria for fusion power performance within operational constraints. Key plasma parameters such as normalised beta, Greenwald density fraction, auxiliary power and radiated power have been scanned to scope the operational space and to derive a collection of candidate non-inductive flat-top points. The assumed auxiliary heating and current drive is either from electron cyclotron systems only or a combination of electron cyclotron and electron Bernstein waves. At present stages of transport modelling, there is a large uncertainty in overall confinement for relevant parameter regimes. For each of the two auxiliary heating and current drive systems scenarios, two candidate flat-top points have been developed based on different confinement assumptions, totalling to four operating points. A lower confinement assumption generally suggests operating points in high-density, high auxiliary power regimes, whereas higher confinement would allow access to a broader parameter regime in density and power while maintaining target fusion power performance.

Unethical Practices in Tanzania Public Universities: Does Workload Matter?

Globally, the operations of universities rely on workload distribution. The extent to which the workload shouldered by employees is excessive or insufficient has implications for ethical behaviour and well-being in academic careers. This paper examined the effect of workload on unethical practices in Tanzanian public universities. Karasek's Job Demand-Control Model served as the foundation for the study. The quantitative research approach was utilized, and questionnaires were used for data gathering. The study adopted a correlational research design. The study gathered data from three public universities intending to reach 245 respondents sampled through stratified sampling who were administered questionnaires, and only a total of 209 respondents completed it. The collected data were considered for analysis through descriptive and inferential statistics. Meanwhile, STATA MP version 17 was used for analysis to conduct the multivariate regression model. The finding revealed workload has a significant positive effect on unethical practices, indicating that both excessive and insufficient workload contribute to unethical behaviour among academic staff. The study concluded that although workload in higher learning institutions is a lifeblood of curriculum implementation, it is not fairly distributed and thus affects both individual and organizational operations. Therefore, the study recommends that the universities should play a crucial role in developing and implementing internal workload policies that link with academic integrity to foster high-quality services in university operations.

Analysis of Regulation of Costs for Operating Buses in a Transport Company

The problem of increasing passenger traffic remains acute for municipal public transport. The value of this indicator is determined by the interest of citizens in this way of making their trips and determines the feasibility of the carrier’s operation. The authors conducted a study of the problems of public transport services in large- and medium-sized cities, which found that the population’s interest in public urban passenger transport has generally been significantly lost. More than 40% of the city population refuses to travel on public transport, half of the population has questions about the reliability of tariff formation, and the same number of people are not satisfied with the regular route network and schedule. City residents increasingly prefer personal vehicles or taxis for their trips, which negatively affects the revenue side of carriers, as well as the level of social comfort and the quality of life of citizens. Efforts to reduce the operating costs of the carrier are aimed at correcting the current situation with urban transport so that tariffs for transportation are more acceptable for passengers. The formation of tariffs for passenger transportation for transport companies is an urgent and complex task. It is necessary to formulate the tariff in such a way as to cover your own transportation costs in the near future and, at the same time, not exceed the psychological threshold for passengers so as not to cause their negative reaction. In addition, since the transportation of passengers by urban public transport is regulated by the authorities, it is also necessary to provide an economic justification for transportation tariffs. This is difficult in the absence of substantiated indicators of consumption rates of material resources in the transport process. To solve this problem, it is necessary to carefully analyze the current costs of operating the bus fleet, as well as forecast costs for future periods. At different periods, researchers have proposed various approaches for planning the cost of operating a bus fleet. The approach we propose is to use standardization of the consumption of material resources, considering the individual operating conditions of the bus fleet and the influence of various factors.

Институт проектного офиса в организациях с бимодальным управлением

Today a lot of attention is paid to project management. This is due both to the special importance of supporting strategic advantage (rapid changes, an objective reduction in the life cycle of modern products and an increase in dependence on customer needs can critically devalue the assets and potential of the organization), and to the need to find solutions to problems without disrupting the overall functioning and taking into account the risks associated with resistance to change. In management practice, projects are often equated with programs and interpreted as a set of pre-planned activities, which requires maintaining the "top" management, providing resources for the implementation of these activities. Meanwhile, the key in projects is budgeting tasks, results of operations, and not activities, individual operations. At the same time, within the framework of the tasks set, the set of their constituent operations should not be administered. If this condition is not met, then there will be no positive effects of the project associated with novelty (discoveries), changes, development. Another innovation of the 21st century for managing the development of organized systems is bimodal management. This article discusses the features of project management in private and public organizations when they use modern bimodal management, as well as the problems of functioning of a special project support structure — the project office. The author's approach to projects as a partnership is proposed, in contrast to a special organization of resource management and operations with a bias towards coordination and control activities, in principle alien to the idea of projects as activities of personally interested persons outside the framework of official or functional duties and powers. The article shows the restrictive conditions of the project method and proposals for overcoming them in the field of public administration.

A unified solution framework for flexible job shop scheduling problems with multiple resource constraints

This paper examines flexible job shop scheduling problems with multiple resource constraints. A unified solution framework is presented for modelling various types of non-renewable, renewable and cumulative resources, such as limited capacity machine buffers, tools, utilities and work in progress buffers. We propose a Constraint Programming (CP) model and a CP-based Adaptive Large Neighbourhood Search (ALNS-CP) algorithm. The ALNS-CP uses long-term memory structures to store information about the assignment to machines of both individual operations and pairs of operations, as encountered in high-quality and diverse solutions during the search process. This information is used to create additional constraints for the CP solver, which guide the search towards promising regions of the solution space. Numerous experiments are conducted on well-known benchmark sets to assess the performance of ALNS-CP against the current state-of-the-art. Additional experiments are conducted on new instances of various sizes to study the impact of different resource types on the makespan. The computational results show that the proposed solution framework is highly competitive, while it was able to produce 39 new best solutions on well-known problem instances of the literature.