Planning Solution Research Articles

Minimal‐cost route planning via Fibonacci‐heap‐typed data structure

AbstractEfficient route planning in transportation networks, particularly under stochastic conditions like severe weather (i.e. snow or hail), poses a significant computational challenge. This article addresses this challenge by modeling the route planning problem as a Markov decision process (MDP) problem, establishing reachability criteria, and identifying the minimum‐weight arborescence in the directed graph. To achieve this, the reachability determination algorithm is designed to assess the courier company's reachability to all junctions based on the queue‐typed data structure and breadth‐first search idea. Subsequently, the minimal‐cost route planning algorithm is developed to find a feasible transport route with the minimal cost of clearing obstacles by resorting to the Edmonds' algorithm and some feasible data structures. In particular, the article introduces a Fibonacci‐heap‐typed data structure to the minimal‐cost route planning algorithm, resulting in a remarkable reduction of the time complexity from to , where and represent the cardinalities of the arc set and nodeset, respectively. Ultimately, the proposed method is applied to optimize route planning in a transportation network, providing a cost‐efficient solution for logistics and transportation planning.

Apartment Layouts of Social Housing for Tomsk Architecture

Apartment layouts define the types of residential cells and their correlation with a multiapartment residential building or residential development. It is one of the main parameters that determines spatial planning in the architectural design of a multi-apartment residential building.Purpose: To formulate recommendations for classification of residential cells of the housing fund for social use, which will be appropriate for the architectural design of a multi-apartment residential building; to determine accommodation of different types of apartments for families registered in the Tomsk regional administrations to improve living conditions. The criteria that determine the place of residential cells in the spatial planning solution of a multi-apartment residential building include the demographic composition of families and mobility of their members.Methodology: Statistical data analysis and diagrams of spatial planning solutions for multiapartment residential buildings, making use of residential cells of one to six rooms.Value: Solutions for housing architecture are proposed through apartment layouts in terms of the spatial planning for multi-apartment residential buildings in the Tomsk social housing.

Investigating the Evolution of Cloud Computing: Research Perspectives

Cloud computing is an economical and powerful tool for small businesses, especially in developing countries. It offers a scalable solution for enterprise resource planning, supply chain management, customer relationship management, healthcare applications, and mobile apps that can reach many users. In this paper, we examine the various concepts associated with cloud computing. Leveraging our experience with different clouds, we explore clouds from technical and business perspectives. We highlight some of the opportunities in cloud computing, emphasizing the importance of cloud technology. This paper provides detailed information about the features, uses, and practical applications of cloud computing.

A Two Phases Multiobjective Trajectory Optimization Scheme for Multi-UGVs in the Sight of the First Aid Scenario.

Timely delivery of first aid supplies is significant to saving lives when an accident happens. Among the promising solutions provided for such scenarios, the application of unmanned vehicles has attracted ever more attention. However, such scenarios are often very complex, while the existing studies have not fully addressed the trajectory optimization problem of multiple unmanned ground vehicles (multi-UGVs) against the scenario. This study focuses on multi-UGVs trajectory optimization in the sight of first aid supply delivery tasks in mass accidents. A two-stage completely decoupling fuzzy multiobjective optimization strategy is designed. On the first stage, with the proposed timescale involved tridimensional tunneled collision-free trajectory (TITTCT) algorithm, collision-free coarse tunnels are build within a tridimensional coordinate system, respectively, for the UGVs as the corresponding configuration space for a further multiobjective optimization. On the second stage, a fuzzy multiobjective transcription method is designed to solve the decoupled optimal control problem (OCP) within the configuration space with the consideration of priority constrains. Following the two-stage design, the computational time is significantly reduced when achieving an optimal solution of the multi-UGV trajectory planning, which is crucial in a first aid task. In addition, other objectives are optimized with the aspiration level reflected. Simulation studies and experiments have been curried out to testify the effectiveness and the improved computational performance of the proposed design.

A Design of Three-Dimensional Spatial Path Planning Algorithm Based on Vector Field Histogram.

In this paper, we present a novel three-dimensional spatial path planning algorithm based on the Vector Field Histogram* (VFH*) approach, specifically tailored for underwater robotics applications. Our method leverages the strengths of VFH* in obstacle avoidance while enhancing its capability to handle complex three-dimensional environments. Through extensive simulations, we demonstrate the superior performance of our algorithm compared to traditional methods, such as RS-RRT algorithm. Our results show significant improvements in terms of computational efficiency and path optimality, making it a viable solution for real-time path planning in dynamic underwater environments.

Thermodynamic functions and parameters of sorption from flue gases (CO2,SOx,NOx) by Khekordzula clinoptilolite

Generation during the production process and emissions into the atmosphere with flue gases (CO2,SOx,NOx) cause the “greenhouse effect” and the problem of global warming. Despite the existing practice of using zeolite as an adsorbent for a number of gases in projects such as Carbon Capture, Utilization and Storage to prevent climate change, the thermodynamic functions and parameters of the zeolite tuff containing the mineral Khekordzula clinophtholite in the inner Kartli region of Georgia are unknown and have not been studied. According to the research data, the corresponding thermodynamic parameters were determined, namely the enthalpy of formation of the mineral clinophthylolite in the Khekordzula zeolite tuff ΔfH2980=−39,825.838kj·mol−1, Gibbs energy ΔfG2980=−36,734.784kj·mol−1, entropy S2980=−10.373j·K·mol−1; Dehydration and as well as physical sorption (CO2, SOx, NOx) start parameters: temperature T=352.90K, pressure P=6.84mmHg. The thermodynamic parameters of the Khekordzula natural clinoptilolite tuff, taking into account its basic mineralogical composition, were determined: ΔfH2980=−30,403.76kj·mol−1; ΔfG2980=−29,963.01kj·mol−1; S2980=−1.48j·K·mol−1; T=374.22K, P=0.0003mmHg. It has been confirmed that chemisorption (CO2, SOx, NOx) by Khekordzula clinophthylolite should begin at temperatures above 2000 K. The results of the conducted studies make it possible to evaluate the prospects of using Khekordzula and natural zeolites of similar composition as an adsorbent for harmful industrial gases, which will help plan and implement effective solutions to environmental problems.

Planning for Introducing Electric Buses Based on Ecological and Financial Impacts

The transition from fossil fuel-powered buses to electric buses has emerged as a central concern in recent years. Governments worldwide are urging this shift in major urban centers as a strategic response to ecological challenges, particularly issues related to pollution and carbon emissions. The primary impediment to the electrification transition lies in real-world financial constraints. Consequently, comprehending both the ecological benefits and financial intricacies of transitioning bus fleets is paramount.In the initial section of this paper, we formulate a mathematical model to assess the reduction in carbon emissions and pollution resulting from a complete transition of the bus fleet. This model is then applied to the city of Sendai, Japan. By comparing the carbon dioxide and emission gases released by conventional buses with those emitted by electric buses, we can discern the impact of employing electric buses on the urban ecological environment.Moving on to the second section, we present a mathematical model delineating the financial aspects of the transition. We use Sendai as a real-world exemplar for our model. The economic model is categorized into expenditures and revenues. Expenditures encompass the acquisition of electric buses, maintenance costs, and carbon taxes. On the income side, we consider bus fares, revenue from bus advertising, the budget of the bus company, and government subsidies. By subtracting expenditures from revenues, we can ascertain the financial ramifications of transitioning to electric buses.Following the evaluation from both ecological and financial perspectives of the bus fleet's electric transition, a third model is constructed mathematically to address the optimal planning solution for a city aiming to fully electrify its bus fleet within a decade. The objective is to achieve cost-efficiency: to be the most economical while meeting ecological goals. Finally, the cities of Sendai, Kunshan, and Nashville serve as subjects for our model, each providing a tailored solution to the transition planning.

From Vision to Reality: The Use of Artificial Intelligence in Different Urban Planning Phases

In an urban context, the use of artificial intelligence (AI) can help to categorise and analyse large amounts of data quickly and efficiently. The AI approach can make municipal administration and planning processes more efficient, improve environmental and living conditions (e.g., air quality, inventory of road damages, etc.), or strengthen the participation of residents in decision-making processes. The key to this is “machine learning” that has the ability to recognise patterns, capture models, and learn on the basis of big data via the application of automated statistical methods. However, what does this mean for urban planning and the future development of cities? Will AI take over the planning and design of our cities and actively intervene in and influence planning activities? This article applies a systematic literature review supplemented by case study analyses and expert interviews to categorise various types of AI and relate their potential applications to the different phases of the planning process. The findings emphasize that AI systems are highly specialised applications for solving and processing specific challenges and tasks within a planning process. This can improve planning processes and results, but ultimately AI only suggests alternatives and possible solutions. Thus, AI has to be regarded as a planning tool rather than the planning solution. Ultimately, it is the planners who have to make decisions about the future development of cities, taking into account the possibilities and limitations of the AI applications that have been used in the planning process.

Gender-inclusive urban planning: European frameworks as a potential methodology for Arabian Gulf urban parks

PurposeThis trigger article explores established European gender-mainstreaming urban planning frameworks of urban parks to analyze and identify ways that could be applied or adapted for Arabian Gulf cities. It aims to accelerate the mainstreaming process, increasing women’s participation and inclusion in urban spaces, paving the way for future research.Design/methodology/approachAnalytical frameworks are created by reviewing legal and policy evolution, city-issued guidelines and European cities’ case studies (Barcelona, Berlin, Paris and Vienna) engaged in gender mainstreaming in urban planning. These analytical tools are then applied to assess two Arabian Gulf parks (Al Azaiba Wadi Park, Muscat, Oman, and Dahl Al-Hamam Park, Doha, Qatar), suggesting a possible future research methodology.FindingsSuccess factors in European cities include integrating female perspectives, detailed user analysis, specific planning solutions and political will. Despite differing social and cultural contexts, commonalities exist for female park users in Europe and the Arabian Gulf. This trigger article proposes a methodology for assessing the potential effective application or adaptation of European established frameworks in the Gulf context to accelerate gender mainstreaming.Research limitations/implicationsThe paper proposes a methodology for future research, noting limitations such as limited input on design preparation processes in Gulf City park case studies, a lack of feedback from park users and only a brief overview of sociocultural differences. Future research should explore nuanced cultural contexts, including historical processes and gender dynamics, thorough literature review, expanded case study analysis and participatory approaches. The proposed methodology aims to demonstrate how European frameworks can guide gender-mainstreaming efforts in diverse contexts, facilitating collaborative solutions for inclusive urban planning.Practical implicationsDrawing from decades of European gender-mainstreaming activities, the paper distills urban planning principles and best practices for application or adaptation in the Arab Gulf.Social implicationsEnhancing the park experience for women through planning and design boosts gender equality in cities, benefiting their physical and social well-being.Originality/valueAn original methodology is suggested for adapting well-developed European gender-mainstreaming frameworks to Arabian Gulf parks. Authored by a male, this paper aims to advance gender issues in planning while exploring the role men can play in contributing to such.

Psychosexual Implications of Tubal Ligation in a Sample of Iraqi Women

Background: Tubal ligation, recognized as a surgical intervention that ensures permanent contraception, has established itself as an option for women seeking a definitive solution for family planning. Objective: To assess the psychosexual implications of tubal ligation in a sample of women in Baghdad, Iraq. Methods: A prospective cohort study was conducted in a teaching hospital for 2 years, from the first of January 2022 to the end of December 2023, in which 203 women who underwent tubal ligation were included. Results: In the present study, we found that 158 (77.8%) had no depression, mild depression presented in 27 (13.3%), and moderate depression in only 15 (7.4%). While 163 (80.3%) of women did not suffer from anxiety, 32 (15.8%) had mild to moderate anxiety, and only 8 (3.9%) were presented with severe anxiety. 27 (13.3%) have changed in coital frequency this this week. 49 (24.2%) have a change in sexual desire, a change in pleasure, and 37 (18.2%) suffer from a change in orgasm. Conclusions: The current study concluded that there are noticeable psychosexual effects of tubal ligation in women.

Methodological Planning and Data Collection. Ensuring a Valid and Credible Research of a Questionnaire Survey in Social Work

The validity and credibility of scientific research are determined by the strictness of planning and elaborating each stage of the research, by correlating the purpose of the research with the chosen research method, by avoiding methodological planning errors, as well as by carrying out each research stage in a manner that excludes errors in data collection, processing and interpretation. In the field of social work, par excellence, the value of an empirical research is conferred, among other things, by the possibility of extrapolating the conclusions of that research to similar situations in the practical activity of social workers, in case work with the beneficiaries of social work services. Due to the close connection between research and practice in this field of social sciences, the methodological design must be transparent and convincing, so as to give practitioners a high degree of confidence in the conclusions of the scientific study, as well as the possibility to capitalize on its informative benefits. So, methodological errors of research projects carried out in the field of social work can have a much wider and more tangible negative impact than in the case of other fields of science, at least from a pragmatic point of view, when theory is translated to practical applicability, and the scientific study is implemented in case work performed with the beneficiaries. This study aims to analyze the questionnaire survey in social work, by highlighting the main methodological errors that can affect the validity of such an empirical study, in order to identify the optimal solutions for a correct planning and methodological development of the scientific study.

Virtual reality-based site layout planning for building design

This paper addresses the challenge of integrating optimized design solutions in Site Layout Planning (SLP) through Virtual Reality (VR), questioning how VR simulations can enhance their acceptance. The methodology involves a multi-objective optimization model that evaluates critical factors like earthwork volume, cost, and environmental impact, integrated into a VR framework for interactive participant evaluations. Results show a notable 48.3% increase in decision-making accuracy among participants using VR, highlighting VR's potential to significantly improve comprehension and application of complex data-driven designs in SLP. This underlines the transformative impact of VR on enhancing stakeholder engagement and optimizing design outcomes. Future research will broaden the participant base and further investigate the long-term effects of VR integration in professional environments.

Integrating carbon and water footprint into nature-based solution (NBS) for urban planning in a highly built-up area in Guangzhou, China

Stormwater management problems have been deteriorated with the high frequency and intensity of precipitation owing to rapid urbanization and climate variability, especially in urban highly built-up area. Nature-based solutions (NBS) have emerged as a powerful measure for rising these challenges due to their ability to mitigate urban waterlogging and increase carbon sequestration. Identifying optimal locations for NBS implementation remains a critical research focus. This study integrates carbon and water footprint accounting into NBS-based planning for sustainable urban development in central Guangzhou, China, to enhance urban flooding mitigation and carbon sequestration. Through carbon-water footprint analysis and weighting, we prioritized NBS planning. To achieve the objectives of increasing sequestered carbon and reducing urban runoff, three types of NBS—green roofs, permeable pavements, and bioretention systems—were optimized for a high-priority town street. The results showed that the implementation of green roof and permeable pavement reduced the surface runoff by 3.58 %, while the biological retention system reduced the runoff gray water by 27 %. Moreover, the application of green roof and biological retention increased the carbon sequestration by 2.57 million kg CO2-eq (life cycle). The findings of this study provide comprehensive insights into optimization of NBS planning based on carbon-water footprint accounting, facilitating to enhance mitigation of urban flooding vulnerability and carbon sequestration.

Integrated solutions for line planning and seafloor surface fitting in marine surveying

Integrated solutions for line planning and seafloor surface fitting in marine surveying

Swift: A Data-Driven Flight Planning System at Scale

Flight planning, a pivotal challenge in the airline industry, strives to achieve economic and flexible scheduling of airplanes to serve designated flight itineraries. As the demand for air transportation soars, traditional planning methods can be inefficient in managing large-scale flights. Thus, we introduce Swift, a data-driven system tailored to enhance the scalability and effectiveness of flight planning. Swift primarily employs the bipartite graph model to derive optimal and economic flight plans for airlines. Our method not only minimizes the number of required planes but also ensures a balanced workload across these planes. Furthermore, Swift offers the capability of dynamic updates to flight plans in response to unexpected incidents at airports, such as bad weather conditions. Besides, Swift incorporates other functionalities like predicting future flight demand and monitoring real-time flight trajectories. Conference participants can interact with this system and explore our flight planning solution in real-world scenarios.

Public service performance in the distribution of cash assistance for female heads of poor households in Semarang City

Background: This paper discusses the performance of public services in the distribution of direct cash assistance (BLT) for female heads of poor households in Semarang City, focusing on the aspects of planning, implementation, and program impact. Methods: The research aims to analyze the effectiveness of the BLT program, evaluate solutions to challenges faced, and formulate recommendations for sustainable improvement. Findings: The research results show that thorough and responsive planning, transparent implementation, and innovative solutions can enhance public service performance. The BLT program has a positive impact on empowering female heads of households through economic strengthening and active participation. Semarang City has successfully created a model of successful public service, providing hope for a higher quality future for female heads of households. Conclusion: Recommendations include increasing digital literacy and evaluating gender-responsive policies to support inclusive and sustainable development. Novelty/Originality of this Study: The study uniquely highlights the specific challenges and successes in the distribution of Direct Cash Assistance (BLT) to female heads of poor households in Semarang City, emphasizing the importance of gender-responsive policies and the empowerment of women. Its originality lies in its detailed focus on planning, implementation, and impact analysis, providing a model for improving public service performance in similar urban settings.

The Methodology for Assessing the 15 Minute Age-Friendly Walkability (AFW) of Urban Public Spaces

Recent decades have witnessed noticeable demographic changes around the world. The global population has continued to increase steadily and, according to forecasts, the trend will be maintained in the coming decades. An increase in the 60+ population is yet another important demographic change. These determinants pose new challenges for socio-economic, spatial, and transport policies in most, if not all, cities in the world. These policies should be aligned with the global development paradigm to promote sustainable development and sustainable improvement of the quality of life of the present and future generations. In the coming years, the potential of cities should be recognized, resources should be managed rationally, effective spatial policies should be implemented, and user-friendly spaces should be created to promote the development of effectively managed urban areas. Cities are often compared to living organisms, which is why social mobility is a crucial determinant of urban development and is often used in assessments of cities. To address the above needs, a universal and innovative methodology for assessing the age-friendly walkability (AFW) of urban public spaces was developed and tested in the present study. The methodology was developed based on a review of the current trends in age-friendly cities, a survey of the target population, and a self-designed concept for evaluating the walkability of pedestrian routes in public space. The proposed methodology not only contributes to the existing knowledge but also has practical implications because it was tested in a Polish city to classify the 15 min walkability of pedestrian routes and to identify Strategic Intervention Areas for the 60+ population (SAI 60+). This innovative approach to walkable urban public spaces is a simple tool for developing senior-friendly planning solutions in cities. The developed paper constitutes a basis for precise spatial planning it is based on reliable data by conducting a full and comprehensive spatial inventory of mobility trajectories of older people walkability. The aim of the undertaken research was to improve the quality of urban residents’ lives in the context of Sustainable Development Goal 11 (to make cities and human settlements safe, stable, and sustainable). Above all, the study is congruous with the sustainable urban mobility vision.

A mission planning method for deep space detectors using deep reinforcement learning

Mission planning for deep space detectors is a pivotal step in the successful execution of detection missions. Traditional planning approaches, which typically compartmentalize mission planning and data transmission scheduling, exhibit limitations in adapting to uncertainties and are often inadequate in responding to unforeseen opportunity targets. This paper introduces a mission planning method for deep space detectors designed to address these challenges. Firstly, a Markov Decision Process (MDP) model is formulated, integrating mission planning and data transmission scheduling, with a consideration for planning balance between detection missions and opportunity targets. Subsequently, a Planning Balance with Proximal Policy Optimization (PB-PPO) algorithm is proposed. The proposed algorithm, based in the Proximal Policy Optimization (PPO) algorithm, integrates an orthogonal initialization algorithm to afford improved control over parameter updates. Furthermore, a dynamic learning rate strategy is implemented to accelerate convergence speed. Experimental results show that, the PB-PPO achieves rewards that are 4.42%, 6.78%, 18.32%, and 26.81% higher than those obtained by compared algorithms. Additionally, the PB-PPO demonstrates the capability to address the planning balance between detection missions and opportunity targets, ensuring stable reward growth even when planning a significant number of opportunity targets. In summary, the PB-PPO integrates of MDP, deep reinforcement learning, and innovative strategies to make it a robust solution for detector mission planning in the complex and dynamic environment of deep space.

Analyzing the Requirements for Smart Pedestrian Applications: Findings from Nicosia, Cyprus

This paper elicits and analyzes the main requirements for Smart Pedestrian applications designed to enhance the pedestrian experience in urban environments by offering optimized walking routes, improved accessibility, and support for social inclusion and connectivity. Utilizing a mixed-methods approach, the research combines qualitative insights with quantitative data analysis based on surveys conducted in two strategically selected urban areas of Nicosia, Cyprus. Through the survey, the requirements and potential use of Smart Pedestrian apps are investigated while accounting for the quality of service of the urban infrastructure in a medium-sized city context. Additionally, the study contrasts the current smartphone applications, as they predominantly facilitate vehicular transportation, with the potential use of ICT/ITS to support pedestrians for sustainable mobility. The findings reveal a significant demand for a Pedestrian Smartphone app, driven by its ability to provide relevant information on optimum pedestrian routes, as well as act as a citizen’s voice for spotting infrastructure problems and improving the pedestrian network. Further, it is also revealed that limitations in the pedestrian infrastructure substantially restrict walking preferences, emphasizing the need for urgent city-level urban planning solutions to support active mobility. Additionally, the research carried out underscores the importance of a sustainable business model to support the successful deployment of Smart Pedestrian apps. Ultimately, the results of the study suggest prioritizing a smart technology leverage with a crowdsourcing social network business model to promote pedestrian mobility, thereby reducing vehicular dependence, enhancing public health, and improving the quality of life. Such an approach would act as catalyst for policymakers to concentrate on sustainability by investing in digital technology for integrated pedestrian networks, fostering the emergence of genuine smart cities.

Improving energy consumption for dynamic intake and exhaust FAÇADES: A new setup design: Part B

Dynamic insulation technology adjusts thermal resistance to reduce building energy consumption in response to climate changes. Sustainable building practices prioritize optimizing the building envelope to enhance energy efficiency and regulate the interaction between indoor and outdoor environments. The previous part of this study (Part A) provided an overview of dynamic insulation technology and its potential effectiveness in Iraqi structures with intermittent heating and cooling. The successful implementation of dynamic thermal insulation necessitates careful planning and design solutions that balance performance and efficiency. This paper (Part B) three wall models (static, dynamic, modified dynamic) to evaluate their thermal performance during the heating season. The results demonstrate that the intake facade achieves a preheating efficiency of 77% for the dynamic wall and 81.8% for the modified dynamic wall at the maximum permissible fresh air limit. This improvement in efficiency enhances the quality and conditions of fresh air intake. Additionally, the modified dynamic wall exhibits a notable 50% reduction in pressure loss compared to the dynamic wall, resulting in lower intake or exhaust fan power and thus energy consumption. The results of this paper will guide the presentation of cooling season results and the experimental aspect of future work, offering valuable insights for further exploration. Practical applications This study aims to enhance the efficiency of dynamic facades by investigating the physical phenomena within wall layers. The paper delves into the determination of optimal airflow patterns within facades, the assessment of airflow path modifications, and the evaluation of energy efficiency achieved by implementing dynamic insulation at the intake and exhaust facades during the heating season. The findings contribute to streamlining design complexities and expanding design options for specific climates, thereby ensuring the pragmatic implementation of this technology.