Achieving sustainable development is a challenge that cities throughout the world have never faced before due to the rapid growth of society and urbanization [
1]. A common goal for the entire world is the pursuit of sustainable urban development [
2], thus prompting a re-evaluation of city dynamics and sparking diverse lines of contemplation on the symmetry and balence within urban environments. At the core of this conceptual exploration lie three fundamental pillars: society, environment, and economy. Cities, grappling with intricate pressures and expectations, demand a reconceptualization and restructuring of the complex interplay between ecology, residents, economy, politics, and society, thus aiming for a balance and symmetry in their development. A greater dependence on the special qualities and opportunities that urban living offers is needed to respond to the changing terrain of urban sustainable development [
3]. Using cloud computing in line with the Tapio Decoupling Principle, Shang and Luo [
4] investigated ways to lessen the impact that cities have on the environment. This was carried out in their University of Texas at Austin study. Xiao et al. [
5] presented a technique that may prove useful in managing urban climates and improving energy efficiency. With the use of private vehicle behavior analysis, this technique forecasts the temperature of urban areas. In addition to fulfilling measurable physical criteria like air quality indices, ratios of green space, population densities, and resource usage, a vibrant and developing city needs to foster human connections and interpersonal exchanges to improve its general quality [
6]. The framework for sustainable development in the twenty-first century, known as Agenda 21 (1992), integrates the environment into the social and economic spheres from the standpoint of the demands of human life. It highlights the fundamental role of a thriving life in sustainable development, thereby considering it the culmination of progress in both environmental and socioeconomic aspects. Aligned with this perspective, the World Health Organization (WHO) initiated the Healthy City (HC) project in 1997, thus aiming to materialize urban sustainable development [
7]. Successive endeavors, such as Eco-City [
8,
9], Green City [
10,
11], Resilient City [
12,
13], Smart City [
14], Inclusive City [
15,
16], and Livable City [
17,
18], echo a global shift towards sustainability in urban development [
19]. An improved method to guarantee the dependability of vehicle-to-vehicle communication in difficult urban situations has been proposed by Sun et al. [
20] as part of their research on distributed routing algorithms for intersection fog in vehicular ad hoc networks. Sun et al. [
21] described an adaptive weighting technique aimed at improving the accuracy and robustness of multisensor-integrated navigation in urban environments.
The multifaceted nature of urban system sustainability encompasses various dimensions intricately woven into the fabric of modern urban living. These dimensions include, among others, resource utilization, environmental conservation, land use efficiency, responsible resource management, economic development sustainability, social well-being, thoughtful living space planning, energy efficiency, climate change resilience, symmetry in urban design, and waste reduction [
22]. Each of these aspects plays a pivotal role in shaping the trajectory of urban development and the well-being of its inhabitants. Xiao et al. [
23] investigated the aggregation effect of private cars through spatiotemporal trajectory analysis, thereby contributing to a deeper understanding of urban mobility patterns. Sun et al. [
24] proposed a bus trajectory-based routing scheme for message delivery in urban vehicular ad hoc networks, thus enhancing communication efficiency in dynamic urban environments. Navigating the inherent complexity of urban systems requires a practical and all-encompassing approach. Navigating the intricate dimensions of cities and translating their diverse interconnected characteristics into actionable models is a complex undertaking that propels tangible development. In terms of the problem, it underlines that two major structural flaws must be corrected. First and foremost, the basic ideas of urban sustainability must be thoroughly examined. Second, it is critical to have a strategy for objectively and effectively investigating the symmetry and complex relationships between diverse components. These sustainability qualities become more complicated as cities grow and change at a rate unprecedented in the globe. In a world characterized by urbanization and environmental issues, cities and scholars are at the forefront of sustainable urban development debates. This makes it a critical global issue requiring a prompt response. However, this will need an awareness of the several aspects associated with rapid urbanization and ecological issues. Understanding these difficulties is insufficient; integrated frameworks that enable comprehensive and sustainable urban development policies must also be established. Given the importance of urbanization and environmental dangers, communication between cities and researchers is essential.
In the constantly shifting environment of urban development, the shared goal of transforming urban areas into foundations of health, sustainability, endurance, intelligence, inclusion, and livability is highly dependent on residents’ personal experiences—an idea often encapsulated in the broader notion of quality of life (QOL). This complicated concept smoothly integrates sociological, economic, ecological, and symmetry considerations defining the fabric of urban life. Because of the world’s pressing ecological issues, sustainable urban development is necessary, and a key success factor in this respect is the quality of life or QOL. Within this framework, attention is focused on the “Life-City” (LC) idea, an inventive framework that goes above and beyond traditional guidelines for urban development. A city is not just a location to meet daily needs; it is also an ongoing process of improving the economy, environmental sustainability, and quality of life.
Xu and Wei [
25] have addressed the dynamic pickup and delivery problem with trans-shipments and Last-In-First-Out (LIFO) constraints. In this study, effective logistics management is covered. Zhang et al. [
26] suggest using an Adaptive Dynamic Surface Control for Electric Vehicles to improve the efficiency and dependability of hybrid energy sources. With this control system, energy management would be improved by the use of disturbance observers. Yang et al. [
27] provided a unique method for predicting the flow of traffic propagation in urban road networks by utilizing multigraph convolutional networks. For planning and traffic control purposes, this approach may prove advantageous. Based on GPS data, Yang et al. [
28] offered a method for accurately anticipating traffic. They achieved this by creating a model for temporal multispatial dependency graph convolutional networks-based region-level traffic prediction. The LC project altered the usual approach to urban planning by viewing cities as evolving ecosystems where life exists in tandem with larger environmental aims. This project acts as a catalyst for ongoing development, thus resulting in an atmosphere in which residents enjoy a vibrant and evolving urban landscape, as well as living in a physical location. Recognizing that increased human connection is critical for sustainable urban growth, the LC initiative seeks to create communities that actively encourage their residents’ thriving well-being while simultaneously being flexible to environmental concerns. It aims to establish a symmetry between human needs and ecological sustainability, thus positioning the city as a living organism that adapts to its inhabitants’ changing needs and plans. The Living City initiative promotes the transformative notion that urban living may be both sustainable and pleasurable for the wide spectrum of people it affects. The aforementioned study addresses a wide variety of decision-making-related issues.
1.1. Literature Review
By studying “fuzzy sets” (FSs), Zadeh [
29] significantly enhanced the ability to make decisions in the face of uncertainty. His mathematical method is incredibly useful for resolving unclear data and provides a useful tool for situations requiring complex decision making. In the face of uncertainty, Zadeh’s FSs offer a flexible yet uncomplicated approach to ambiguity analysis. Atanassov [
30] made a significant advancement when he created “intuitionistic fuzzy sets” (IFSs), which comprise assessments of both membership and nonmembership traits. This enhanced adaptability is useful when making difficult choices. The addition of nonmembership components to IFSs is particularly relevant when making decisions when there is a substantial deficiency of high-quality information. Cuong [
31] worked on “picture fuzzy sets” (PFSs), which added to the decision-making process. These visual representations enable a more realistic integration of human perspectives into decision models. Furthermore, Cuong and Hai’s [
31,
32] developments in current operators and features boost the notion of PFSs and provide decision makers (DMs) with more accurate tools.
Li et al. [
33] proposed novel ideas, including extended reduced neutrosophic Einstein AOs and a unique distance metric for fuzzy collections of Cubic Picture Fuzzy Sets (CPFSs) [
34,
35]. Ashraf et al. [
36] introduced the concept of SFSs, which go beyond PFSs and Pythagorean sets. This extension in SFSs enhances the precision of fuzzy set models, thus redefining membership degrees as
, which deviates from the traditional formulation of
in PFSs. The authors explored the basic operations that affect SFSs and expanded upon them to add aggregated operators to further convey these ideas. Weighted averaging and weighted geometric aggregation operators are two examples of novel aggregation operators that they investigated, which show versatility in a variety of decision-making scenarios. By introducing fresh viewpoints and useful tools that significantly expand the precision and flexibility of decision-making models, their significant study expands the use of fuzzy set approaches. The authors’ investigation of these new ideas shows how dedicated they are to extending the possibilities of fuzzy set theory and its application to decision theory.
To enhance the decision-making process, Gündodu and Kahraman [
37] developed a spherical fuzzy TOPSIS examination and presented the concept of SFSs. Kahraman and Gündodu [
38] proceeded further to investigate decision making using SFSs and advanced to a more comprehensive understanding of their application. SFSs were employed by Mahmood et al. [
39] to solve medical diagnostics and decision-making challenges, thus showcasing their adaptability to a range of domains. Ullah et al.’s study [
40] examined similarity metrics for T-SFSs and offered insights into pattern identification applications. Furthermore, Gündodu and Kahraman [
41] increased the amount of data on SFSs by presenting a novel spherical fuzzy analytical hierarchy approach and highlighting its use in renewable energy contexts. Taken collectively, these studies deepen our knowledge of the theory, methods, and real-world applications of SFSs in several fields. The SWARA approach was established in the study of Keršuliene et al. [
42], which concentrated on choosing an equitable conflict settlement using a stepwise weight assessment ratio analysis. In their investigation of the fuzzy SWARA approach in multicriteria decision making (MCDM), Stević et al. [
43] used SWARA to provide an unbiased assessment and yielded unsatisfactory findings. In a spherical fuzzy environment, Ghoushchi et al. [
44] evaluated wind turbine failure scenarios utilizing SWARA-CoCoSo models, thus contributing to the renewable energy industry. Ayyildiz et al. [
45] presented a methodology relevant to environmental management by integrating SWARA and DEA for the performance analysis of wastewater treatment plants. Ulutaş et al. [
46] used the plithogenic SWARA approach to assess logistics risks. Wang et al. [
47] suggested a multisensor system that uses measurement quality control to help cars navigate in urban environments. This technology increases navigation accuracy by carefully adhering to quality criteria while merging sensors. Zhang et al. [
48] created a multitask learning framework aimed at improving environmental monitoring and management through semantic and instance segmentation in coastal urban spatial perception. An attention mechanism was incorporated into this framework. Xu and Guo suggested a novel approach for calibrating DVLs [
49]. The foundation of this technique is a strong, invariant, extended Kalman filter. This technology improves the accuracy of the velocity estimation of underwater vehicles.
Zavadskas and Turskis [
50] made significant advancements to MCDM by developing the WASPAS model. This innovative method can be especially helpful in navigating challenging circumstances, since it gives DMs a systematic and weighted framework for assessing and ranking options based on a wide range of criteria. Apart from its theoretical contributions, the WASPAS model has been effectively applied by academics and practitioners to tackle actual choice issues, thus demonstrating its practical significance across many fields. The work of Zavadskas and Turskis [
51] shows how their work improves decision making in a variety of fields and not only supports the theoretical foundations of MCDM but also offers a useful and adaptable instrument to improve decision making. Ma et al. [
52] demonstrated autonomous pipeline navigation of a cockroach biorobot with enhanced walking stimuli, thus showcasing advancements in bioinspired robotics for challenging environments. Xu et al. [
53] investigated the influence of fintech, digitalization, and green technologies on sustainable development in CIVETS nations, thus providing evidence through comprehensive approaches. Liu et al. [
54] presented SS-DID, a secure and scalable Web3 decentralized identity system utilizing multilayer sharding blockchain, thus enhancing privacy and scalability in decentralized systems. Pan et al. [
55] applied location–allocation modeling to rational health planning, thus evaluating spatial accessibility improvement of tertiary hospitals in a metropolitan city of China and contributing to better healthcare resource allocation.
The accuracy of rankings within the WASPAS system was revisited by Baykasoglu and Gölcük [
56] in their work. Their study investigated the validity and consistency of the WASPAS model for rating choice alternatives, thereby adding to the current discourse in the field of cybernetics. Our comprehension of the method’s efficacy in real-world applications has been improved by this study. Keshavarz et al. [
57] presented a novel approach to decision making that utilizes Fermatean fuzzy sets and WASPAS. Their research was centered on evaluating suppliers for green buildings. Particularly in light of environmentally conscious activities in the construction sector, their paper offers insightful information about how the WASPAS model might be used to evaluate suppliers. Badalpur and Nurbakhsh [
58] added to the body of literature by qualitatively analyzing risks using the WASPAS approach. Their case study, which centered on a road construction project in Iran, provides useful insights into the application of the model for assessing and controlling risks related to construction projects.
Using an integrated MCDM methodology, Seker and Aydin [
59] evaluated hydrogen generation strategies in the presence of uncertainty. By assessing alternate models for producing hydrogen via the WASPAS approach, the work advances the science. Lin et al. [
60] conducted asymptotic analysis for one-stage stochastic linear complementarity problems and applications, thereby offering theoretical insights into optimization problems with practical implications. Liu et al. [
61] proposed mechanism design for blockchain storage sustainability, thus addressing challenges and providing solutions for sustainable blockchain systems. W. et al. [
62] explored limited sensing and deep data mining for the development of citywide parking guidance systems, thus highlighting advancements in intelligent transportation systems. This work contributes to our understanding of decision-making difficulties in ambiguous contexts. To choose an overseas payment mechanism, Nguyen et al. [
63] provided Spherical Fuzzy WASPAS-based Entropy Objective Weighting. Their study focused on decision making in global payment and finance systems, thus enhancing the objectivity of weighing models by combining the WASPAS method with SFSs.
These studies include the use of deep learning and edge cloud computing for risk assessment in China’s international trade and investment [
64], the MCDM model for evaluating road section safety [
65], and the application of interval-valued picture fuzzy uncertain linguistic Dombi operators in industrial fund selection [
66]. These studies demonstrate a variety of approaches to risk management and decision making in a variety of contexts. The study’s findings offer important information that may be used to the field of decision making regarding renewable energy. Advanced decision-making methods, including Fermatean fuzzy aggregation operators [
67] and Pythagorean fuzzy Hamacher aggregation operators [
68], have been highlighted along with their applications and contributions to various fields, including the FMEA-QFD for risk assessment in distribution processes [
69]. Dede and Zorlu [
70] evaluated geoheritage by employing the entropy-based WASPAS model. They specifically focused on the Karcal Mountains, which are located in Turkey. Their research contributes to the subject of geoheritage evaluation by presenting a method for evaluating and rating geoheritage sites by utilizing the WASPAS model. They employed the WASPAS and TOPSIS methodologies to investigate these factors. Their research sheds light on the potential benefits and drawbacks of implementing cutting-edge technology in the construction industry, thereby providing valuable information that can be utilized by professionals in the field. Their research contributes to the advancement of the field of geoheritage assessment by providing a framework for evaluating and rating geoheritage sites based on the WASPAS methodology. The findings of their study provide practitioners in the construction industry with insights into the opportunities and challenges that are associated with the implementation of modern technology in the industry.
A major advancement in decision-making framework development has been the expansion of the SWARA-WASPAS approach to SFSs. This is especially true in cases when the interpart interactions are intrinsically complex and multidimensional. On the surface of a unit hypersphere, membership values can be established by applying SFS theory. A more nuanced and adaptable definition of ambiguity and uncertainty is provided by this expansion compared to the conventional method. Compared to regular fuzzy sets, SFSs provide DMs with a more holistic view of the choice environment by representing the complex interdependencies across decision criteria in a multidimensional space. This enhancement allows the SWARA-WASPAS approach to handle complex and variable choice scenarios with more ease. Pattern recognition and similar domains often face such situations, since linear fuzzy sets can not capture relationships well enough. This expanded framework shows promise in enhancing decision quality and enabling more knowledgeable and efficient decision-making processes in complex and uncertain situations by combining the strengths of SFSs with SWARA-WASPAS’ systematic and reliable decision-making methodology.