Optimal Cost Research Articles

Surgical treatments of lymphedema-a literature review on robot-assisted lymphovenous anastomosis (LVA).

Lymphedema is a common issue after surgery and oncologic treatment, affecting millions of people worldwide. A better understanding of the condition has provided an increasing possibility of a tailormade treatment plan, and with improvement in surgical technique, we now have several surgical treatments to offer, including the lymphovenous anastomosis (LVA). Considering the size of lymph vessels used for LVA, sometimes as small as 0.3 mm, there is a need for improvement of the technical aspects of the procedures. This paper explores the potential of robotic assistance in LVA surgery as an innovative approach to overcome the limitations of human dexterity. A literature review was performed on 2023-12-22 using PubMed, Cochrane, and Embase databases to identify all previous publications on robotic LVA surgery, resulting in a total of 65 publications. Original publications in English were considered and after selection, a total of 5 publications were included in the review. Two surgical systems used in clinical practice were identified, the MUSA (Microsure) and the Symani Surgical System (Medical Microinstruments). Common topics for discussion include the increased precision the robot assistance provides, clinical outcomes, ergonomics, and the learning curve for aspiring robot surgeons. Anastomosis times were generally found to be longer initially, but several authors note that there is a steep learning curve with rapidly decreasing times with an increasing number of procedures. Overall clinical outcomes were comparable to those using manual anastomosis. The use of robotics in LVA surgery, has shown promising results through clinical studies. Robotic assistance can help augment the technical capacity of a surgeon through motion scaling and tremor filtration, facilitating the most delicate steps of the LVA. The learning curve is steep, and the technique can hopefully make microsurgical reconstructions available to a broader number of patients. Further development can include haptic feedback, structured training programs, and cost optimization through dissemination of the technology.

Application of the Least Cost Analysis Method to Determine the Optimal Cost and Duration for Delayed Projects

The construction project of the Polresta Denpasar Multi-Purpose Building experienced delays due to the Eid al-Fitr holiday, resulting in a 9.35% setback, equivalent to 19 days. In the 20th week, the planned progress was 66.52%, but actual progress was only 57.17%. With 76 days remaining for the project's completion, the least cost analysis method was applied to find the optimal cost and time for completing the remaining work by increasing the workforce. This approach aims to ensure the project is completed on time and the contractor avoids penalties. The penalty is 1/1000 (1 ‰) of the contract value. The analysis used primary data such as interviews and project observations, and secondary data including contractor unit price analysis, budget plans (RAB), and S-curves. The data was analyzed from the remaining project work, crashing duration, to finding the cost slope for each task, and then using the least cost analysis method to determine the optimal cost and time. The analysis results showed that the optimized project cost after acceleration was Rp 3,077,713,130.90, with the project duration reduced from 76 days to 57 days, accelerated by 19 days. This acceleration saved costs by Rp 18,428,493.93. By applying this method, the project is expected to be completed faster without compromising quality, and the contractor can avoid delay penalties. This approach helps in time efficiency and budget management, ensuring all resources are used optimally and the project is completed on target.

Determination of the impact of innovative technologies in the system of strategic management of corporate social responsibility

The object of research is the process of using innovative technologies in the system of strategic management of social responsibility of enterprises. The main problem solved during the research was the need for a more effective integration of the principles of social responsibility in the business strategy, which will help enterprises to adapt to the global challenges and demands of modern society. The study of new technological approaches in this area allowed to identify the most effective tools for increasing transparency, responsibility and sustainable development of companies. As a result of the conducted research, the content of the concept «innovative technologies in the system of strategic management of social responsibility of enterprises» was clarified, which is proposed to be understood as a modern approach to the integration of technological innovations into strategic management, aimed at improving the social indicators of the enterprise. These technologies are found to include a wide range of tools such as Big Data, Artificial Intelligence (AI), Internet of Things (IoT), Blockchain, and others that help businesses effectively implement and monitor social programs and initiatives. It is substantiated that the use of innovative digital technologies in the system of strategic management of social responsibility of enterprises opens wide opportunities and generates significant advantages. Namely, increasing transparency and openness; optimization of resources and costs; increasing internal efficiency; strengthening of reputation and brand; automation of enterprise processes; innovativeness and competitive advantages; stimulating innovation. A model for determining the relationship between the level of profitability of enterprises by type: large, medium, and small enterprises and by the number of employees and their labor costs is proposed, which allows to establish the required number of employees for each type of enterprise. This enables the enterprise to function effectively, reducing labor costs, but not reducing the positive impact on supporting the social sector of the population, creating jobs and remaining a socially responsible enterprise. The possibility of using the latest digital technologies in the social responsibility management of enterprises is summarized.

Principles of Cloud Computing Infrastructure IaaS

Infrastructure as a Service (IaaS) represents a cornerstone in contemporary cloud computing, providing essential on-demand computing resources, including servers, storage, and networking. This paper explores the foundational principles of IaaS, highlighting its ability to facilitate dynamic server management through practices like auto-scaling and ephemeral server utilization. The use of custom images in IaaS ensures minimal downtime and scalable deployment, while loose coupling enhances fault tolerance and adaptability. Emphasizing high availability through auto-scaling, IaaS supports continuous operations even in geographically vulnerable areas. The security framework of IaaS, encompassing a shared responsibility model, ensures robust data protection and compliance with industry standards. The paper also addresses cost optimization strategies and the integration of hybrid cloud architectures to maximize resource efficiency and maintain data integrity. Overall, IaaS is integral to modern IT infrastructure, offering flexible, scalable, and cost-effective solutions that align with the evolving demands of the digital landscape.

Optimizing Distribution Center Network Design for a Cosmetic Manufacturer: A Case Study on Lightening Series Package Product

Ensuring customer satisfaction while maintaining optimal cost efficiency is paramount in designing a successful supply chain structure. This study explores the vital role of service quality and delivery efficiency in achieving customer satisfaction and a superior overall experience through a cost-effective supply chain structure. Furthermore, the strategic positioning of Distribution Centers (DC) and the geographical distribution of consumers serve as additional determinants in the quest to devise the most effective DC scheme that meets consumer expectations. Four simulation scenarios, each with measurable parameters including response time, lead time, and operational costs, were evaluated to identify the most cost-efficient and responsive solution. These parameters encompassed the performance metrics of the supply chain structure model, namely response time and lead time, in conjunction with the total operational cost of each scenario. Our findings reveal that scenario 1 emerges as the most cost-effective with the lowest distribution costs and shortest customer lead time. This scenario consistently maintains the lowest distribution costs from the first to the seventh year. Despite a surge in forecasted demand in the 7th year, resulting in an increase in total distribution costs to Rp. 3,392,793,440, scenario 1 still prevails with overall vehicle costs decreasing and the smallest percentage cost at 17.50%, thus yielding the most economical outcome compared to alternative scenarios. Scenario 4 offers a similar outcome to scenario 1 but incurs higher daily vehicle operating costs. The cost-effectiveness demonstrated by scenario 4 further highlights the significance of strategic DC placement in achieving optimal supply chain outcomes.

Taguchi Method for Optimizing Economic Product Selling Prices in MSMEs Concrete Industry

This article examines research related to determining the economic selling prices for concrete brick products at Karunia MSMEs, with the aim of optimization for production cost while still maintaining process quality. The method used in this research is Design of Experiment (DoE) based, namely Taguchi with regression, then continued with cost analysis to determine the optimal cost of production for efficiency. The technique in this method uses 3 variables, there are sand, cement and the length of time for mixing the concrete mixture with the quality parameters and production costs of the concrete bricks. Based on the experimental results, in achieving the goal of increasing cost efficiency, through sensitivity analysis it was obtained that the optimal composition of the cost of production was IDR 5,000 per piece of concrete brick, while maintaining SNI quality standards in optimal results of compressive strength is 117.37 kg/cm2, water permeability is 7.77% and roughness is 52.42 µm. The cost of production is the same as the initial cost of production before composition optimization efforts are carried out, where the initial concrete brick product is indicated as not meeting SNI quality standards because it has a compressive strength value below standard. The results of this research are expected to be able to provide recommendations for economic selling price for concrete brick by production costs optimizing while maintain the SNI standard quality of concrete brick products.

A multi-objective mixed integer linear programming approach for simultaneous optimization of cost and resilience of power distribution networks

In recent years, customers have experienced a significant increase in weather-related power outages. The power distribution network (PDN), a subset of the power system, in particular is more susceptible to extreme events. Therefore, ensuring the resilient and cost-effective operation of PDNs following extreme weather conditions poses a significant challenge for distribution network operators. This paper presents an approach for simultaneously optimizing the cost and load restoration for resilience enhancement of power distribution networks while determining the optimal positioning and generation levels of mobile emergency generators. The proposed method, in addition, employs a distribution network reconfiguration to improve the load restoration process, by optimally determining the status of switches. The multi-objective formulation involves the minimization of load shedding to increase the resilience of the system, while the other objective is formulated to minimize the cost of load restoration. A weighted sum method is employed to address the multi-objective mixed-integer linear programming (MILP) model. A set of non-dominated solutions determined using the proposed formulation provides opportunities to the distribution system operator in choosing a resilience improvement strategy according to the availability of the operational budget. The proposed model is implemented on 33-bus distribution system to validate the efficacy of the proposed model.

The Evolution of the Theory of Innovation Ecosystems in the Context of Strategisation

Introduction. The theory of innovation occupies one of the leading positions within the modern paradigm of economic development, as innovation is recognised as a driver of productivity improvement and cost optimisation, microeconomic stability, and macroeconomic growth. The determinants of innovation theory have become more profound, forming a synthesis with theories of economic cycles, technological development, entrepreneurship, management, and decision-making. Consequently, the theory of innovation has evolved, and the study of this process provides an up-to-date view of the theoretical foundation of innovation ecosystems. Aim and tasks. The aim is to systematise the stages of the evolution of the theory of innovation and strategic management and formalise the theoretical foundation of the modern theory of innovation ecosystems in the context of strategisation. Results. A systematic study of the genesis and ontogenesis of the theory of innovation and anagenesis of the theory of innovation ecosystem in the context of strategisation led to the determination of the characteristics of aromorphosis. Genesis and ontogenesis include the growing complexity of the innovation ecosystem and its adaptability to the changing innovation ecosystem in the long term, the dynamism of the composition of the innovation ecosystem without changing its strategic goals, the need for a second level of adaptation of the strategy of an individual actor within the strategy of the innovation ecosystem and strategic role, and increasing the integration of actors of the innovation process into systemic business processes (planning, organisation, motivation, control). Actors’ joint development within the ecosystem on mutually beneficial terms and possibilities for the strategic expansion of the innovation ecosystem locally and globally were analysed. In addition, the externalities of the development and spread of innovative ecosystems are outlined, and their strategic orientations are formulated. Conclusions. Due to anagenesis, an innovative ecosystem based on strategising improves adaptive resistance to changes in the external environment. Aromorphosis of an innovative ecosystem within anagenesis makes it possible to consider the properties of adaptation to the changing innovative ecotope as the basis of its theoretical foundation in the long term, the dynamism of the composition of the innovation ecosystem without changing its strategic goals, and the increasing integration of innovation process actors into systemic business processes.

Multi-Objective Optimization in Support of Life-Cycle Cost-Performance-Based Design of Reinforced Concrete Structures

Surveys on the optimum seismic design of structures reveal that many investigations focus on minimizing initial costs while satisfying performance constraints. Although reducing initial costs while complying with earthquake design codes significantly ensures occupant safety, it may still cause considerable economic losses and fatalities. Therefore, calculating potential earthquake damages over the structure’s lifetime is essential from an optimal Life-Cycle Cost (LCC) design perspective. LCC analysis evaluates economic feasibility, including construction, operation, occupancy, maintenance, and end-of-life costs. The population-based, meta-heuristic Ideal Gas Molecular Movement (IGMM) algorithm has proven effective in solving highly nonlinear mono- and multi-objective engineering problems. This paper investigates the LCC-based mono- and multi-objective optimum design of a 3D four-story concrete building structure using the Endurance Time (ET) method, which is employed for its efficiency in estimating structural responses under varying seismic hazard levels. The novelty of this work lies in integrating the ET method with the IGMM algorithm to comprehensively address both economic and performance criteria in seismic design. The results indicate that the proposed technique significantly reduces minor injury costs, rental costs, and income costs by 22%, 16%, and 16%, respectively, achieving a total reduction of 10% in all structural Life-Cycle Costs, which is considered significant.

Cost Optimization of Graphene Oxide-Modified Ultra-High-Performance Concrete Based on Machine Learning Methods

The use of carbon nanomaterials in ultra-high-performance concrete (UHPC) to improve its mechanical properties and durability is growing. Graphene oxide (GO) has emerged as one of the most promising nanomaterials in recent years for enhancing the properties of UHPC. The majority of research so far has been on the properties of UHPC enhanced with GO, but its high cost has limited its application in engineering. This work suggests a machine learning (ML)-based approach to optimize the mix ratio in order to lower the cost of graphene oxide-modified UHPC. To do this, an artificial neural network (ANN) is used to create the prediction model for the 28-day compressive strength and slump flow of UHPC. The performance of this model is then compared using nine different ML techniques. Subsequently, considering the restrictions of the UHPC component content, component proportion, and absolute volume, a genetic algorithm (GA) is adopted to lower the UHPC cost. The sensitivity analysis is carried out in the end. This study’s findings indicate that there is a decent degree of prediction accuracy since the difference between the ANN model’s predictions and the experimental outcomes is just 10%. The cost of UHPC optimized by GA is reduced to 776 $/m3, significantly lower than the average cost of UHPC.

Modelling the impact of introducing first-generation narrowbody hydrogen aircraft on the passenger air transportation network in Europe

The global aviation industry faces a pronounced challenge to mitigate its contribution to anthropogenic climate change, which is caused by burning fossil fuels. One potential pathway is the transition towards using green hydrogen as zero-carbon fuel. Next to technological, infrastructural, and economical challenges, this would introduce a wide range of operational and infrastructural changes to a system centred around safety and reliability. This study employs a holistic approach and examines these changes from a flight network perspective, focusing on passenger transport in Europe. It utilizes network modelling and linear optimization techniques to determine network changes imposed by the introduction of first-generation narrowbody hydrogen aircraft. The findings are threefold: First, the study shows that the air transportation network can be adequately re-created using demand and direct operating cost optimization only, without considering revenue and airline-specific factors. Second, the introduction of hydrogen aircraft will have substantial impact on network structure, incl. flight frequency, capacity, and stopover routes, depending on seat capacity and range of the hydrogen aircraft design. Lastly, it also shows that airports that have a favourable green hydrogen supply will benefit from the introduction of hydrogen aviation.

Holacratic management models in organizational systems

This article presents research results of holacratic models implementation for high-tech sector of Russian and foreign markets. The relevance of conceptual models implementation to organizational systems is caused by a competition of effective business models and continuous costs optimization of high-tech enterprises. The problem of a rapid transition from classical cascade and divisional models to holacratic ones is forced by the needs of management methods and models that will ensure high-quality process and economic changes without a negative impact on the supply chain and the process of creating goods or services with a high added value for modern enterprise economy. This research presents a comparison of classical management methods in organizational systems versus holacratic ones. The problem analysis considers the mathematical features of comparing existing management models. Achieved results presented in this article indicates that the need of the methodology for rapid transition to holacratic management models in organizational systems is beginning to emerge including development of a conceptual mathematical model for an ideal holacratic organization. Functional and process gaps during transition to a new management model including mathematical aspects under given conditions can be considered as the conclusion for research.

Current issues of animal welfare and health in pig breeding (review)

Objective. To summarise current issues related to welfare and health in pig production. Methods. Domestic and foreign sources of literature on the subject of research and their desk analytical analysis. Results. Today, animal welfare is determined by a combination of three interrelated components: the physical, mental and natural state of certain animals, as well as, of course, humane human attitude to meeting their needs. Until recently, the problems of humane treatment ofproductive animals were exclusively related to economically developed countries where intensive livestock production technologies were used. Pig farms need to have highly productive animals, adequate and balancedfeed, and use resource-saving technologies to produce breeding and marketable products at the optimum cost. Improving the efficiency of pig production primarily has a negative impact on the welfare of pigs. At the same time, it should be understood that, in general, pigs are raised to produce meat and lard products, which is directly related to their slaughter and, accordingly, the taking of their lives. Therefore, the needs of pigs will not be fully met. However, the basic needs - the so-calledfive freedoms of animals - must be met. A detailed grouping of approaches to determining animal welfare is formed in three main aspects: physical condition, mental condition and naturalness. It should be borne in mind that the satisfaction of specific needs in the natural environment does not always ensure their full satisfaction in the two aspects ofphysical and mental health. In the case of pig breeding, it is necessary to take into account the consequences of long term targeted selection of the main breeds and significant modification of their representatives compared to wild forms. The provision of air, water and feed for pigs is critical and should be provided in full. However, this is not always taken into account on Ukrainian pig farms. In addition, the welfare of pigs is inextricably linked and directly depends on the health of the animals. Conclusions. The review of literature sources to summarise current issues related to welfare in pig production indicates that there are a number of issues to be addressed in Ukraine. First and foremost, we are talking about EU legislation that should be implemented in domestic production, which is especially relevant on Ukraine's path to full EU membership. With regard to the existing pig welfare issues, the list of methods and approaches for determining certain indicators is gradually expanding, but it should be borne in mind that welfare in pig production is not limited to pig housing. These are issues related to the transport and slaughter of pigs, aspects that synergise with the subsequent safety of pig products. Of particular importance are the issues in which pig welfare intersects with biosecurity and ensuring appropriate animal health. Key words: pigs, welfare, animal health, housing, feeding, productivity, commercial pork production.

Network Design and Control: Shape and Topology Optimization for the Turnpike Property for the Wave Equation

The optimal control problems for the wave equation are considered on networks. The turnpike property is shown for the state equation, the adjoint state equation as well as the optimal cost. The shape and topology optimization is performed for the network with the shape functional given by the optimality system of the control problem. The set of admissible shapes for the network is compact in finite dimensions, thus the use of turnpike property is straightforward. The topology optimization is analysed for an example of nucleation of a small cycle at the internal node of network. The topological derivative of the cost is introduced and evaluated in the framework of domain decomposition technique. Numerical examples are provided.

Guided optimization: a fast model-based nested cost optimization technique for existing product family designs

Guided optimization: a fast model-based nested cost optimization technique for existing product family designs

Hydraulic Analysis and Cost Optimization of Water Network by Using the EPANET Software

The large water network leads to a large set ofnonlinear equations that need to be solved by either byHard Darcy or Newton Raphson methods. Those twomethods need a large code to analyze and simulate thenetwork which takes large time. EPANET software can do ahydraulic analysis of the water network. In addition, thesoftware can run with time duration which means that theresult can be obtained as function in time. However, writinga code gives the result in the steady state manner becausethe Bernoulli’s equation was derived under the assumptionof steady state. In this paper, a hydraulic analysis of waternetwork of town of about 7000 population under an area of0.6 km2and 2125 m3/day water demand is done by gettingthe nodal pressure, pipe discharge, and total head at thesignificant time hour of the day by using the EPANETsoftware. Also, an optimization is done to minimize theenergy cost of the electricity by the investigation of whatminimum level that the tank discharge water without usinga pump. Therefore, nine hours make the network operate bygravity main and 15 hours by pumping main. That can bedone only by EPANET software result table that show howmany hours that can make the pump off instead of using itthe whole day. The energy cost minimized by 38 %.

Target reliabilities for heritage structures derived from cost optimization

AbstractIn the last decade, structural reliability and safety efforts have been oriented toward the assessment of existing structures and the development of related target reliability levels. However, up‐to‐date there is no consensus on the reliability philosophy that should be followed when considering the assessment of heritage structures, and the level of reliability which is appropriate to them. In this study, a framework is proposed which derives new values for the economically optimal target reliability for the upgrade of a structure, , and the reliability threshold for upgrade, , considering the cultural heritage value of the structure. The total expected life cycle cost is minimized, assuming that the structure is given up after collapse, as heritage value is typically lost after failure. The target reliability values are based on three main parameters: the relative annual benefit of using the structure (affected by its heritage value), the relative cost of failure and the relative cost of increasing the reliability. Target reliability values are proposed specifically for heritage structures, considering a range of the main input parameters.

Efficient neural network-aided seismic life-cycle cost optimization of steel moment frames

In this paper, a novel and efficient neural network-based methodology is proposed to achieve seismic total cost optimization of steel moment-resisting frames in a timely manner. The computational burden of an optimization process based on performing nonlinear time-history analysis is prohibitively high. To address this crucial issue, a new and efficient neural network model is proposed in this paper to accurately predict the nonlinear time history response of steel frames during the optimization process. In the proposed neural network model, an ensemble of parallel neural networks is used to provide excellent prediction accuracy. In addition, a new repairability constraint is proposed to check the seismic damage level of structures during the optimization process with the aid of the proposed neural network model. Moreover, an efficient metaheuristic algorithm is used to achieve the optimization task. Two numerical examples are illustrated to demonstrate the efficiency of the proposed methodology. The results show that the proposed neural network model outperforms the existing standard models in terms of prediction accuracy. Furthermore, it is shown that by using the proposed methodology, the optimal seismic total cost of steel frames increases by less than 2.5%, yet their seismic collapse capacity increases by at least 30%.

Evolutionary Dynamics of Passive Housing Initiatives in New Rural Construction

In the context of China’s ambitious dual carbon goals, this study introduces an innovative reward–penalty incentive mechanism, grounded in evolutionary game theory, to develop a tripartite evolutionary game model concerning the construction of passive rural housing. This research meticulously analyzes the equilibrium and stability strategies of all involved parties and employs data simulation to examine the influence of varying parameters on the game dynamics. Our findings reveal that the government’s cost–benefit calculations significantly influence its decisions regarding passive housing initiatives. The study identifies optimal cost and benefit strategies for various developmental phases. Furthermore, the level of governmental rewards and penalties plays a crucial role in determining whether enterprises and farmers opt for passive housing solutions. The study establishes the efficacy of different incentive schemes at various stages. Importantly, the economic interests of enterprises and farmers are pivotal in their decision-making process regarding passive housing. The study advocates for a comprehensive set of measures to safeguard these interests, with a special emphasis on protecting farmers. In conclusion, this research offers substantial guidance for policy decisions aimed at transforming existing rural housing into passive housing, thereby aligning with China’s environmental and sustainability objectives.

НАУКОВО-МЕТОДИЧНІ ЗАСАДИ РЕСТРУКТУРИЗАЦІЇ ВИРОБНИЧОГО ПРОЦЕСУ

Batch production is typical for engineering enterprises connected with aeronautical engineering manufacturing. One of its main problems is the need to periodically change the production pattern which arises as a result of the instability of the products range, changes in volume of series, moral and physical wear of technological equipment. Such a change is carried out in the course of reconstruction and technical re-equipment in order to improve the efficiency of material flows.The main characteristics of material flows are determined by a spatial component of a flexible manufacturing system pattern, set by the machine tools laying according to the organization of batch process. The bulk of the cost of final product manufacturing is associated with the arrangement of material flows. In order to reduce the total costs it is necessary to improve the pattern of production by establishing a technology-oriented machine tools laying. In this case, there is a need to develop scientific and methodological basis of restructuring the manufacturing process.One of the most effective approaches to the design of machine building plants with a batch type of manufacturing is the use of program-target method based on the methodology of choosing the best technological solutions.Modern methodology of batch technologies design is based on the system approach to the analysis and synthesis of the basic structure of the manufacturing processes, which allows to apply mathematical simulation.The orientation of each of the sites on the end result leads to a substantial reduction of manufacturing costs, which significantly simplifies solving problems of division and coordination of labor on the principles of self-organization and self-regulation.The proposed mathematical model of manufacturing costs optimization is designed in accordance with all the aforementioned principles. The problem being solved is multiobjective. That is why the mathematical model has several goal functions them requiring finding peak values and some of them requiring finding the bottom values.The model can be applied in organizing the aeronautical engineering manufacturing, which requires effective remounting during the change of product range thus ensuring the required flexibility of manufacturing.