Flexible Planning Research Articles

Hybrid parameter-based PSO flexible needle percutaneous puncture path planning

Hybrid parameter-based PSO flexible needle percutaneous puncture path planning

Flexible time horizon planning, learning and aggregate fluctuations

A dynamic general equilibrium model is constructed and analyzed under the assumptions that the representative decision maker is endowed with incomplete knowledge about his environment of interest along with limited cognitive skills. Under various beliefs about the long-run growth prospects consistent with Kaldor's, 1961 stylized facts, the benchmark infinite-dimensional decentralized planning problem collapses into infinite sequences of T>1 dimensional sub-problems which are each within the decision maker's limited computing range. Based on the time length of the planning horizon and the nature of expectations, the resulting framework in which both forecasts and plans may get revised in the light of new information encompasses at the limits the benchmark infinite horizon case with perfect foresight, a rolling infinite horizon case, a self-fulfilling static planning case and Day's, 1969 two-period heuristic case. Under exogenous price and quantity growth forecasts consistent with the perfect foresight steady-state balanced growth path, the time length of the planning horizon may have no effect on the resulting competitive equilibrium which may deviate dramatically from the optimal solution. When these growth forecasts are endogenous, the competitive equilibrium effects of the planning horizon time length depend on the characteristics of the information sets. The resulting model may help us to better understand how economies respond to shocks by unraveling new propagation mechanisms related to changes in optimism or pessimism about short-run and/or long-run growth prospects.

Inclusive Play: Defining Elements of Playful Teaching and Learning in Culturally and Linguistically Diverse ECEC

Inclusive values are integral to early childhood education and care (ECEC) policies, promoting equal participation opportunities and individual support for all children. Play serves as a method for meaningful engagement, mutual cultural knowledge creation, and learning within ECEC. Pedagogical play entails teachers’ observation, interaction, support, and guidance. This study investigates practical elements and methods employed by teaching staff and experienced by children during playful activities. Conducted as a case study in two culturally diverse ECEC centers during spring 2023, data collection involved video-recorded monitoring of children’s daily activities in five groups. Video data were transcribed and analyzed using content analysis tools to identify categories of inclusive play. Findings are presented as narratives to honor children’s experiences. The study identifies five elements of inclusive play: teachers’ active participation and presence, balanced repetition with flexible plans and adaptive goals, playful language fostering joy in play, non-verbal and kinesthetic communication with enabling tools, and emerging play marked by interaction and lasting intensity. These elements reveal opportunities and challenges for children’s inclusion and learning approaches, informing recommendations for promoting inclusive play in ECEC. Inclusive play emphasizes diverse strategies accommodating differences in learning styles and modes of knowledge expression among teaching staff and children.

Evaluation of Virtual Student Activities: Basis for the Enhancement of the Flexible Student Activity Plan

Evaluation of Virtual Student Activities: Basis for the Enhancement of the Flexible Student Activity Plan

COWORKING SPACE DI KOTA PONTIANAK DENGAN PENDEKATAN PRINSIP FLEKSIBILITAS DALAM ARSITEKTUR

The freelancer profession in the current era is in great demand by many people. In the world of freelancing, income and place of work are not fixed. Most freelancers have little business capital in leveraging skills and building relationships. In addition, freelancers do not have a limit on working time, but are free to determine where to work. Freelancer activity facilities in Pontianak City do not support convenience. They are active in cafes or coffee shops with a low level of privacy. Freelancers and other creative industry players need a place that is comfortable for their activities, both working, socializing, and collaborating in running their business. They need a container that fits their activities, namely coworking space. Coworking space is a multifunctional workplace that combines various commercial functions, such as offices, meetings, culinary, entertainment, and others. For this reason, it is necessary to design a coworking space in Pontianak City. The purpose of a coworking space is to accommodate various work activities, both individually and in groups, along with their supporting activities. The design method used is flexibility in architecture, including adaptable and universal space. The steps used are looking for problems, identifying, collecting data, analyzing, conveying ideas, selecting ideas, designing products, and evaluating. The expected result is a flexible spatial plan inside and outside the coworking space, adapting to the dynamics of freelancers and other users.

A decision-making method for the operation flexibility enhancement of hybrid cascaded MTDC

To enable the integration of large-scale renewable energy, hybrid HVDC technology, which combines the technical advantages of LCC-HVDC and VSC-HVDC, is being gradually deployed in the power grid nowadays. The operation of the Wu-dong-de Hybrid DC Project and the Jian-su Hybrid cascaded MTDC Project has proved its advantages. However, for the simultaneous application of different converter station technologies in the system, the control strategies become complex. Issuing appropriate control instructions to ensure system stability according to operational requirements is an issue that cannot be ignored in decision-making. Even under abnormal conditions, when the topology changes due to various failure scenarios, reasonable decision-making and precise control instruction definitions are required. To achieve flexible planning of the MTDC system, this paper presents a decision-making method for control strategies of a hybrid cascaded MTDC system, which analyzes the control strategy combinations selected for normal and abnormal conditions of the MTDC system. In addition, a control instruction calculating method and decision-making process for precise control in normal and abnormal control conditions is proposed. Simulation results based on a five-terminal hybrid cascaded MTDC in PSCAD/EMTDC have verified the effectiveness of the proposed method.

Symmetric Graph-Based Visual Question Answering Using Neuro-Symbolic Approach

As the applications of robots expand across a wide variety of areas, high-level task planning considering human–robot interactions is emerging as a critical issue. Various elements that facilitate flexible responses to humans in an ever-changing environment, such as scene understanding, natural language processing, and task planning, are thus being researched extensively. In this study, a visual question answering (VQA) task was examined in detail from among an array of technologies. By further developing conventional neuro-symbolic approaches, environmental information is stored and utilized in a symmetric graph format, which enables more flexible and complex high-level task planning. We construct a symmetric graph composed of information such as color, size, and position for the objects constituting the environmental scene. VQA, using graphs, largely consists of a part expressing a scene as a graph, a part converting a question into SPARQL, and a part reasoning the answer. The proposed method was verified using a public dataset, CLEVR, with which it successfully performed VQA. We were able to directly confirm the process of inferring answers using SPARQL queries converted from the original queries and environmental symmetric graph information, which is distinct from existing methods that make it difficult to trace the path to finding answers.

STAGES OF FORMATION OF A NETWORK OF GENERAL SECONDARY EDUCATION INSTITUTIONS IN A RURAL LOCATION OF UKRAINE

The study conducted a retrospective analysis of the genesis, formation and development of a general secondary education institutions network in rural areas of Ukraine. Taking into account the broad socio - cultural and political contexts, stages of rural schools network formation related to the emergence of a network (stage 1), its functioning (stage 2), transformation and consolidation of the existing network (stage 3) were revealed, development of the existing network at the expense of active development low -complex schools and schools with low -content classes (stage 4), new enlargement of the school network (stage 5). It is determined that the emergence of a rural schools network is related to democratic trends both by the totalitarian state and by the local initiative from below - by provincial and county zemstvos. And in the stages of formation of a schools network, dynamic and cyclical fluctuations from the democratic principles of formation from below and taking into account the interests of the population in formal administration by a totalitarian state are traced. The dependence of the formation of a schools network and its quality on the state policy on the formation of the system rural population and territorial-administrative reforms is established. The tendency of increasing enlargement of the schools network and cultural and household services in rural areas has been identified, which in turn leads to inequality of access to the services of rural and urban population and accordingly causes the outflow of the population from the villages. The need for more flexible planning of the network, taking into account local features, the need for individualization of approaches to the formation of networks in different territorial communities and regions, which can be facilitated in recent years by domestic scientists network models of integration, cooperation of educational institutions and complex training of various age groups. In order to achieve the goals of sustainable development of the country, it is necessary to form an effective network of pre -school and extracurricular education institutions, general secondary education, creating conditions for the possibility of learning throughout life. Keywords: school network, general secondary education institution, rural school, school building.

Monte Carlo tree search-based deep reinforcement learning for flexible operation & maintenance optimization of a nuclear power plant

Nuclear power plants (NPPs) are required to operate on a flexible profitable production plan while guaranteeing high safety standards. Deep reinforcement learning (DRL) is an effective method to find the most profitable operation & maintenance (O&M) strategy to adopt in a complex system. However, profit-driven only DRL neglects safety-related issues. In this paper, we propose a DRL approach to solve single-objective sequential decision problems (SOSDPs) and multi-objective sequential decision problems (MOSDPs) to find O&M strategies that trade off reliability and profit. The combinatorial problem related with the training of the RL agent to search for the optimal solution is addressed by Monte Carlo tree search (MCTS), whose performance is compared with the traditionally adopted proximal policy optimization (PPO) & imitation learning (IL). A case study is considered for demonstration.

Apartment Space Planning Directions for Infectious Disease Prevention and Management: Insights Based on Residents’ Experiences

The COVID-19 pandemic has raised people’s interest in pandemic-safe housing. This study aims to present insights into apartment housing space design to prevent and manage infectious diseases based on the actual living experiences of apartment residents. The relevant literature was reviewed, and overall satisfaction was assessed through a questionnaire targeting apartment residents in South Korea. Finally, using the photovoice method, residents’ space needs were identified. By applying a mixed-use methodology and identifying the needs of residents, the following two recommendations were derived: (1) a flexible space plan to support multifunctional use while securing work efficiency and privacy in the living room, bedroom, and space for hobbies/work/learning; (2) a facility for removing contaminants at the entrance with sufficient storage space. The residents emphasized the importance of non-structural changes to the space and the convenience of use to increase actual space utilization. When planning future pandemic-safe apartment housing spaces, it is important to consider structural aspects like functionality and facilities. Convenience of use and methods of supporting family members’ privacy should also be taken into account.

Improved crow search algorithm for optimal flexible manufacturing process planning

The enhancement of manufacturing processes due to the growing demand for products and services is a problem that must be constantly updated. Several schemas have been conducted to improve the manufacturing processes. These schemas are based on the flexible use of machines, tools, and tool access directions to determine the best process planning (PP) for a specific piece or part. The combination of different tools and machines leads to the formulation of complicated combinatory problems that can be treated as optimization problems. On the other hand, bioinspired optimization techniques have been widely employed for solving several complex engineering and real-life problems showing competitive results. The crow search algorithm (CSA) is an optimization technique based on the intelligent foraging behavior of crows. Our work uses an improved CSA (ICSA) to determine the optimal flexible process planning (FPP) with a low computational effort. Several AND/OR networks FPP problems are employed in the experimentation stage, where the production cost and production time are considered as fitness functions. To determine the performance and accuracy of the proposed technique, different results previously reported in the literature are used for a comparison showing that ICSA-FPP is able to outperform similar approaches.

A Comparative Study of the Military Tactics of the Mongol Empire and Goguryeo Kingdom (Goryeo)

Abstract The study is conducted as a comparative study of military tactics of the powers representing different regions and time periods throughout human history. Despite the differences in circumstance and time, common success factors are identified in the military tactics of the two great powers. Based on these success factors, it is possible to compare the military tactics of these armies using the following common criteria: basic tactical unit system, strategic flexibility, tactical mobility, and strategic planning. The Mongol Empire and Goguryeo Kingdom had long been the dominant military powers in their regions. Also, during the Goryeo Dynasty, which succeeded Goguryeo, the Mongolian army invaded Goryeo and used there creative military tactics. Especially, the Mongol army was one of the greatest in human history, and through its power and military skill, led to the magnificent growth of the Mongol Empire. Thus, this study identifies the success factors of the Mongol military tactics through comparison with Goguryeo military tactics.

Flexible renewable energy planning based on multi-step forecasting of interregional electricity supply and demand: Graph-enhanced AI approach

Jeju Island faces curtailment problems when renewable energy generation exceeds the facility capacity. In addition, the renewable energy system cannot achieve consistent operation because of the uncertainty of renewable energy sources (RES) and their complex spatiotemporal patterns. Climate change and extreme meteorological phenomena also affect the energy system of the island. Therefore, it is essential to maximize RES exploitation to accomplish carbon-free energy production. This study developed a rolling horizon optimization–based flexible renewable energy distribution planning (FxRE-Plan) based on an artificial intelligence-driven spatiotemporal RES prediction model. An adaptive graph convolutional recurrent network (AGCRN) was used to develop a spatiotemporal prediction model. Then, FxRE-Plan was determined using a multiobjective genetic algorithm to maximize the RES potential under climate change scenarios. The FxRE-Plan was evaluated and compared with the current operation of the electric grid in Jeju Island through economic, environmental cost, and climate change vulnerability assessment index. The results of this research show that the AGCRN–based spatiotemporal prediction model exhibited superior prediction performance, achieving a 95% R2. In addition, the FxRE-Plan reduced greenhouse gas emissions by approximately 11.5% at maximum and climate change vulnerability. Hence, the proposed FxRE-Plan can be used to solve curtailments in real electric grids by pursuing carbon-free islands.

Position-attitude coupling guidance and control for asteroid landing with a flexible lander

Landing on an asteroid is a highly valuable endeavor accompanied by significant challenges, making it a promising area for further research. This paper aims to present a flexible lander specifically designed for asteroid landing missions while also studying the guidance and control techniques involved in its descent phase. Firstly, the paper briefly introduces the mission simulation model and asteroid environment from previous work. It then provides a detailed exposition on the guidance model which facilitates trajectory planning and the attitude control model used for managing the lander's attitude. The parametric trajectory is subsequently applied to obtain the position-attitude coupling trajectory that allows for the flexible lander's trajectory planning. The generating set search method is used to optimize the parametric trajectory under the appropriate constraints, ensuring high efficiency. In tracking the proposed trajectory, an open-loop control is applied for position tracking, while a closed-loop attitude controller is proposed for attitude control. An attitude control technique involving a combination of the nonsingular sliding mode control method with RBF to capture perturbations and unmodeled dynamics is adopted, and its global stability is proven using a Lyapunov-based approach. Monte Carlo simulation is conducted to test the performance of the proposed trajectory planning technique with results showing that real-time trajectory generation and refreshing are achieved. The feasibility and accuracy of the proposed guidance and control technique are further verified with another set of Monte Carlo simulation. Finally, the paper highlights one successful scenario including the descent and touching phases of asteroid landing with the flexible lander, illustrating its feasibility further.

Competing for space? A multi-criteria scenario framework intended to model the energy–biodiversity–land nexus for regional renewable energy planning based on a German case study

BackgroundThe need to balance renewable energy supply with biodiversity conservation has become increasingly urgent in light of current climate, energy, and biodiversity crises. However, the development of wind and solar energy often presents trade-offs such as competing for land use and potentially impacting species and habitats. To address these concerns, ‘priority zones’ for bird and bat species have been proposed as spatial designations for early species protection in the regional planning process. However, there are concerns that the areas suitable for wind and solar energy may be limited further, making it difficult to meet state- and regional-specific spatial targets for renewable energy sites.ResultsTo help decision-makers deal with this challenge, a Multi-Criteria Scenario Framework has been developed and analyzed. It involves a habitat model of priority zones for species conservation and techniques from the intuitive logic scenario planning method. Through a regional case study, various planning criteria were analyzed according to scenarios, such as priority zones for species protection, settlement buffers, and forests. The framework indicates how criteria could be balanced to achieve wind energy spatial targets as well as targets for ground-mounted solar energy with the least possible impact. Results show that compared to other planning criteria, species priority zones had limited competition with spatial wind energy targets. Achieving these targets may require minimal adjustments, such as allowing wind energy in 1–3% of completely protected recreational landscapes. To reconcile land use demands in the energy transition, a balance between ‘green’ protected areas is necessary. Additionally, ground-mounted solar energy could replace some of the wind energy spatial targets while also meeting the overall solar development goals.ConclusionsThe framework provides transparency in assessing trade-offs between multiple objectives and helps quantify the ‘costs’ and ‘benefits’ in renewable energy planning. Adapting more flexible planning methods could help resolve the conflict between wind energy and species protection. Joint analysis of the areas needed for wind and solar energy and determining the optimal energy mix are gaining in importance. However, how the benefits of multi-criteria scenarios can be achieved within the confines of preoccupied and siloed organizations remains an ongoing research topic.

Planning context: Flexible plans and mayoral authority in French urban planning

In this article, I consider the relationship between urban planning and context by investigating the planning practices associated with a land-use plan in Bordeaux described as “adapted to context.” Invested with flexible rules, the plan description followed a tendency in French urban planning concerned with being strategic, prospective, and participatory. It was also the result of metropolitan planning. Through an ethnographic account, I show how local politicians’ references to context related to concerns with mayoral authority in times of planning powers transferred to the metropole. Using permit reviewers’ skills, mayors mobilized flexible rules to manipulate building permit decisions prepared in compliance with the metropolitan plan. It is widely acknowledged that urban planning is affected by as well as affecting different contexts. I outline a complementing approach by drawing on engagements with context in anthropology and STS-scholarship, to propose that the practices associated with the same notion in Bordeaux are telling of how urban planning contributes to making contexts. Since calls for context direct attention and shape which issues and local communities are prioritized, these insights on the relationship between planning and context urge attention to how appeals to context, as never value-neutral or ready-made, gain importance across different urban planning issues and settings.

Robust design of a logistics system using FePIA procedure and analysis of trade-offs between CO2 emissions and net present value

The problems of flexible planning of the design of logistics systems for the collection of food products such as raw milk can result in a decrease in the performance of critical indicators for their performance. This paper proposes a new efficient methodology for robustly designing a first-mile logistics system for storing and refrigerating milk as a perishable product considering decisions related to open facilities and the flow of products, including sustainability indices. The proposed approach is modeled as a bi-objective problem by considering the minimization of greenhouse gas emissions (CO2) produced by milk transportation canteens and the maximization of the system configuration's net present value (NPV). We have analyzed and determined the most robust configuration for the first time and explained the robustness-NPV and robustness-CO2 relationships. The proposed mathematical model is solved by the Epsilon constraints method, and the robustness is calculated considering an extension of the FePIA methodology for multiobjective problems. A novel contribution is a balance in the possible future values generated by the company related to its cash flows and the generation of CO2 emissions when using a motorized transport frequently used in the shipment of raw milk considering a new important aspect such as the volume of product transported and the slope of the path between the production farm and the storage cooling tanks.

Flexibility resource planning of a power system considering a flexible supply–demand ratio

Aiming at the problems of insufficient power system regulation capacity and lack of flexible resources caused by source-load uncertainty, the flexible resource planning of power systems is studied with the goal of improving flexibility. Uncertainty and flexibility are combined in this article, and a probability index of an insufficiently flexible supply-demand ratio is proposed based on the probability characteristics of flexibility. A bi-level programming model of power system flexibility resources considering the probability of an insufficiently flexible supply demand ratio is constructed. Optimal economics is used as the objective function of the planning layer, and the proposed minimum probability index of the flexible supply-demand ratio is used as the objective function of the operations layer. Economics and flexibility are studied, taking the power system in a certain area in Northeast China as the research object. A flexible resource planning scheme that meets different flexibility expectations is obtained, and the scheme is discussed in detail from the aspects of system flexibility, economic cost, and new energy consumption capacity. The effectiveness of quantitative indicators and planning methods are verified.

AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes

The existing resource allocation policy for application instances in Kubernetes cannot dynamically adjust according to the requirement of business, which would cause an enormous waste of resources during fluctuations. Moreover, the emergence of new cloud services puts higher resource management requirements. This paper discusses horizontal POD resources management in Alibaba Cloud Container Services with a newly deployed AI algorithm framework named AHPA - the adaptive horizontal pod auto-scaling system. Based on a robust decomposition forecasting algorithm and performance training model, AHPA offers an optimal pod number adjustment plan that could reduce POD resources and maintain business stability. Since being deployed in April 2021, this system has expanded to multiple customer scenarios, including logistics, social networks, AI audio and video, e-commerce, etc. Compared with the previous algorithms, AHPA solves the elastic lag problem, increasing CPU usage by 10% and reducing resource cost by more than 20%. In addition, AHPA can automatically perform flexible planning according to the predicted business volume without manual intervention, significantly saving operation and maintenance costs.

Deep reinforcement learning for optimal planning of assembly line maintenance

Discovering the optimal maintenance planning strategy can have a substantial impact on production efficiency, yet this aspect is often overlooked in favor of production planning. This is a missed opportunity as maintenance and production activities are deeply intertwined. Our study sheds light on the significance of maintenance planning, particularly in the dynamic setting of an assembly line. By maximizing the average production rate and incorporating flexible planning windows, buffer content, and machine production states, a unique problem is addressed in which a policy for planning maintenance on the final machine of a serial assembly line is developed. To achieve this, novel average-reward deep reinforcement learning techniques are employed and pitted against generic dispatching methods. Using a digital twin with real-world data, experiments demonstrate the immense potential of this new deep reinforcement learning technique, producing policies that outperform generic dispatching strategies and practitioner policies.