Search Results (125)

This paper addresses the formation assignment problem for heterogeneous UAV swarms in dynamic mission environments. A constrained optimization model is constructed in which UAV capabilities are divided into shareable and exclusive types; a neighborhood collaboration decay factor captures the locality of capability complementarity; and a Cobb–Douglas production function evaluates position-specific effectiveness under bottleneck constraints. The objective dynamically trades off deployment costs and system risks through threat-adaptive weight adjustment. To solve the model, a Hybrid Adaptive Large Neighborhood Search (HALNS) algorithm is proposed, integrating an adaptive destroy-repair mechanism, a mathematical-programming-based local search, and an incremental re-optimization strategy for rapid dynamic response. Experiments verify that HALNS attains globally optimal solutions on small-scale instances and outperforms mainstream baselines on medium-to-large problems. The collaboration mechanism raises system effectiveness by an average of 34.75% across four mission scenarios. Compared with static re-optimization, the incremental strategy improves dynamic response performance by 58.25% while reducing runtime by up to 56.7%. Sensitivity analyses confirm the robustness of key parameters. This work provides a theoretical and algorithmic foundation for intelligent UAV swarm assignment and reconfiguration. Full article

This paper estimates an extended Cobb–Douglas production function for five major economies (China, the EU, India, the Russian Federation, and the USA) over the period of 1990–2023, incorporating electricity production from renewable, non-renewable, and nuclear sources as discrete production inputs. To capture complex properties in time series, a comprehensive econometric strategy is adopted, which combines linearity tests, multiple detection of structural changes, linear and nonlinear unit root tests, autoregressive distributed lag (ARDL) bounds testing for cointegration, error correction modelling, and error correction model (ECM)-based Granger causality. The results confirm the presence of mixed orders of integration, nonlinear dynamics, and structural instability across countries, justifying the use of the ARDL framework. The bounds test reveals a long-run cointegrating relationship between output, capital, labour, and energy inputs in all five economies. Long-run elasticities differ significantly across countries, highlighting strong structural heterogeneity. The short-term dynamics show that energy shocks have asymmetric and country-specific effects on output, while the error correction terms confirm convergence towards the long-run equilibrium, with the fastest adjustment observed in the EU and the slowest in the US. The causality results support the hypothesis of growth-led energy in China, India and the Russian Federation, while two-way feedback is observed in the EU and the US. These findings suggest that energy policy cannot be uniform across countries and must be aligned with domestic production structures, technological intensity, and energy transition stages. Full article

Economic entropy, as an emerging concept in econophysics, has gained increasing relevance in the analysis of complex systems characterized by uncertainty, nonlinearity, and out-of-equilibrium dynamics. However, its integration into conventional economic modeling—particularly in production functions such as the Cobb–Douglas function—remains fragmented and lacks systematic empirical validation. This study conducts a scientometric analysis of 345 Scopus-indexed documents (1973–2024) addressing the intersection between entropy, econophysics, and production functions, with the aim of mapping the intellectual structure of the field, characterizing its growth trends, identifying its core contributions, and highlighting its main research gaps. The results reveal that the field has experienced sustained growth since 2004, with a notable acceleration between 2020 and 2023, although it exhibits a fragmented authorship structure that does not conform to Lotka’s Law, suggesting that the field is still in a stage of scientific consolidation. The Cobb–Douglas function emerges as a niche topic within the econophysics literature, with limited integration between entropy-based approaches—informational, thermodynamic, and maximum entropy—and the empirical modeling of production. Furthermore, weak citation linkages between econophysics and conventional economics are observed, confirming the interdisciplinary fragmentation of the field. These findings provide a structured reference for researchers interested in advancing toward analytical frameworks that explicitly incorporate uncertainty, information, and physical constraints into economic analysis, thereby contributing to the development of econophysics as an integrative discipline. Full article

Background: Global supply chains operate in increasingly volatile and technology-intensive environments shaped by digital transformation and artificial intelligence integration. While prior research has emphasized structural and technological enablers of flexibility, the behavioral foundations of supply chain adaptability remain insufficiently explored. Methods: This study develops a conceptual integration of the Kano model and the Cobb–Douglas production function to position managerial attitude as a strategic “delighter” within supply chain systems. The proposed framework models supply chain flexibility as a function of capital, labor, artificial intelligence integration, and managerial attitude within an extended economic representation. Results: The model suggests that managerial attitude acts as a behavioral amplifier that strengthens the performance effects of technological and economic inputs, potentially generating nonlinear gains in responsiveness and adaptive capacity. By distinguishing human-driven, algorithmic, and hybrid attitudinal configurations, the framework clarifies how behavioral orientations influence artificial intelligence adoption and supply chain flexibility, particularly in small and medium-sized enterprise contexts. Conclusions: Although conceptual in nature, the framework provides a formal analytical foundation for future empirical testing and elasticity-based sensitivity analysis in supply chain research. Full article

Urban network externalities have emerged as a novel impetus for regional economic growth. However, the extent to which inter-urban network connections promote regional economic growth and the associated spatiotemporal heterogeneity remain underexplored. This study constructs a multi-dimensional urban network framework from the perspectives of enterprise linkages, infrastructure connectivity, and innovation collaborations, capturing the multifaceted nature of intercity relationships and their critical role in shaping regional development. Utilizing the Cobb–Douglas production function and the spatial Durbin model, the study quantitatively assesses the impact of urban network externalities on economic growth and examines the spatiotemporal heterogeneity of these impacts. The main findings are as follows: Urban network externalities generally exert a positive influence on regional economic growth, yet this effect exhibits significant regional and city-size heterogeneity. Regions with more developed networks experience stronger growth effects from these externalities. Moreover, large cities benefit more substantially from network integration compared to small and medium-sized cities. Spatial decomposition of effects further reveals that urban network externalities promote economic growth through both local direct effects and spillover effects to neighboring areas. Approximately 70% of the economic growth contribution originates from direct effects within the region, while nearly 30% stems from spillover effects from adjacent regions. Additionally, the spatial spillover effects display clear distance decay, following an inverted U-shaped pattern with a bimodal distribution. Significant spillover effects are observed within 380 km, peaking at 180 km and 340 km. Full article

This study focuses on a class of optimization problems about higher education costs with industrial production characteristics, in which the objective function is a quadratic cost function and the nonlinear constraints follow the Cobb–Douglas form. Through variable substitution, this class of nonlinear-constrained optimization problems is converted into optimization problems with linear constraints. Further, this study derives the conditions for the existence of optimal solutions to this optimization problem and conducts numerical simulations for the two-variable scenario to demonstrate its applicability in the field of higher education. Full article

Governmental organizations, projects, and initiatives in Saudi Arabia have focused specifically on the fisheries and the aquaculture sector to reduce reliance on imports, achieve self-sufficiency, and significantly contribute to food security. To accommodate the annual population increase, Saudi Arabia needs to enhance its fish production. This study aims to illustrate the impact of credit on the fisheries sector by examining the factors that affect fish output in Saudi Arabia, both in general and in specific contexts. The research employed annual time series data to estimate the Cobb–Douglas production function. The study computed the Cobb–Douglas model in an error correction format due to the stationarity characteristic of the data. The results show that fish production in Saudi Arabia is significantly enhanced by the number of fishermen, marine fisheries, aquaculture farms, and financial resources. Furthermore, the results reveal that economies of scale play a crucial role in the Saudi fishing industry. Nevertheless, since the data indicates that the influence of marine fisheries on fish output in Saudi Arabia in the long run surpasses that of aquaculture farms, the researchers recommend an increase in aquaculture production. Sustainable methods for fish production, such as minimizing overfishing and bycatch, improving water and environmental quality, and promoting the traceability of fish populations, should be prioritized in the advancement of the fisheries sector. Full article

The olive flounder (Paralichthys olivaceus) is a significant aquaculture species in Korea, yet production has stagnated due to rising costs, environmental pressures, and shifting consumer preferences. Enhancing farm efficiency is critical not only for economic viability but also for environmental sustainability, as efficient production reduces resource waste, lowers feed inputs, and minimizes the carbon output of aquaculture operations. This study estimated the production function and efficiency of olive flounder farms in Korea using stochastic frontier analysis, drawing on survey data collected directly from producers. Results indicate that the Cobb–Douglas model is more suitable than the translog model for empirical analysis. The average farm efficiency was 0.38, with the lowest recorded efficiency at 0.13. Key determinants of production efficiency included fry quality, workforce size, and feed management. Regional differences were also observed in the technical inefficiency factor. By identifying inefficiencies and management gaps, this study highlights opportunities to enhance resource use efficiency, reduce environmental and economic waste, and promote more sustainable practices. The findings provide insights for policymakers and farm managers seeking to strengthen both the profitability and sustainability of the Korean olive flounder aquaculture industry. Full article

This research develops and applies the IoTRIM model to assess the economic and operational implications of IoT integration in postal and courier enterprises in Slovakia. Combining a multi-criteria evaluation framework with an extended Cobb–Douglas production function, the analysis captures both readiness levels and their translation into output performance. The IoTRIM assessment reveals heterogeneous distributions of strengths across four strategic and technical pillars, with notable disparities between connectivity, data analytics, and interoperability capacities. Monte Carlo simulations under pessimistic, realistic, and optimistic scenarios highlight divergent digital trajectories among enterprises, with some demonstrating accelerated gains from IoT readiness while others face structural bottlenecks in infrastructure and process integration. Hypothesis testing indicates that while a positive and statistically significant relationship between IoT readiness and output is observed in selected cases, this effect is not universal across all enterprises and scenarios. However, the inclusion of IoT readiness consistently improves the explanatory power of the production function models. The findings underline that digital transformation outcomes depend not only on investment scale but also on systemic absorption capacity, including interoperability, data governance, and organizational alignment. The proposed approach offers both a methodological contribution for measuring digital readiness impacts and practical insights for strategic planning in the postal and courier sector. Full article

With rapid economic development and the growing global demand for water resources, the relationship between water demand and economic growth has become a critical international concern. This study investigates the role of water resources in China’s economic growth by extending the Cobb–Douglas production function to include investment, labor, energy, land, and water resources. Using national and regional data from 1949 to 2023, we quantify the spatiotemporal dynamics of factor contributions across primary, secondary, and tertiary industries. Results show that investment remains the dominant growth driver, with rising contributions from energy and land, while labor is increasingly substituted. Water resources exhibit marked industrial and regional heterogeneity: since 2013, water constraints have intensified in the primary sector of the Yellow River basin and Northeast China, and in the secondary sector of the inland northwest and Yellow River provinces. Considering national food security imperatives and given the complementary nature of water–land resources and the fixed nature of land, we propose strategic water network planning based on land productivity patterns to optimize resource coordination and drive high-quality economic development. Full article

This paper investigates the symmetric and asymmetric effects of renewable and non-renewable energy on Greece’s economic growth within an extended Cobb–Douglas production function for 1990–2022. The study is motivated by the rising role of renewable energy and the need to determine whether the energy–growth nexus is linear or nonlinear, an issue of central importance for policy. The Brock–Dechert–Scheinkman (BDS) test confirms the nonlinearity of the variables, while Zivot–Andrews unit root tests with structural breaks capture crisis-related disruptions. The Wald test indicates that renewable energy has an asymmetric long-run relationship with growth, whereas non-renewables exert symmetric effects. To model these dynamics, the Nonlinear Autoregressive Distributed Lag (NARDL) framework is applied. Results show that in the long run, positive shocks to renewable energy enhance growth, while both positive and negative shocks to non-renewables have symmetric impacts. In the short run, only non-renewable energy shocks significantly affect growth. Asymmetric causality analysis reveals a bidirectional relationship between positive renewable shocks and growth, suggesting a virtuous cycle of renewable expansion and economic performance. The study contributes by providing the first systematic evidence for Greece on the nonlinear energy–growth nexus, advancing empirical modeling with NARDL and break-adjusted tests, and highlighting the heterogeneous growth effects of renewable versus non-renewable energy. Full article

In this work, we consider the problem of minimizing a quasi-convex function over a nonempty closed convex constrained set. In order to approximate a solution of the considered problem, we propose delayed star subgradient methods. The main feature of the proposed methods is that it allows us to use the stale star subgradients when updating the next iteration rather than computing the new star subgradient in every iteration. We subsequently investigate the convergence results of sequences generated by the proposed methods. Finally, we present some numerical experiments on the Cobb–Douglas production efficiency problem to illustrate the effectiveness of the proposed method. Full article

This study investigates the complex dynamics of new-type urbanization in resource-based county-level cities, using Wuan City in Hebei Province, China, as a representative case. As China pursues a high-quality development agenda, cities historically dependent on resource extraction face profound challenges in achieving sustainable and inclusive urban growth. This research employs a multi-method approach—including Theil index analysis, industrial shift-share analysis, a Cobb–Douglas production function model, and a composite urbanization index—to quantitatively diagnose the constraints on Wuan’s development and assess its transformation efforts. Our empirical results reveal a multifaceted situation: while the urban–rural income gap has narrowed, rural income streams remain fragile. The shift-share analysis indicates that although Wuan’s traditional industries have regained competitiveness, the city’s economic structure is still burdened by a persistent negative structural component, hindering diversification. Furthermore, the economy exhibits characteristics of a labor-intensive growth model with inefficient capital deployment. These underlying issues are reflected in a comprehensive urbanization index that, after a period of rapid growth, has recently stagnated, signaling the exhaustion of the city’s traditional development mode. In response, Wuan attempts an “industrial transformation-driven new-type urbanization” path. This study details the three core strategies being implemented: (1) incremental population urbanization through development at the urban fringe and in industrial zones; (2) in situ urbanization of the existing rural population; and (3) the cultivation of specialized “characteristic small towns” to create new, diversified economic nodes. The findings from Wuan offer critical, actionable lessons for other resource-dependent regions. The case demonstrates that successful urban transformation requires not only industrial upgrading but also integrated, spatially aware planning and robust institutional support. We conclude that while Wuan’s model provides a valuable reference, its strategies must be adapted to local contexts, emphasizing the universal importance of institutional innovation, human capital investment, and a people-centered approach to achieving resilient and high-quality urbanization. Full article

This paper develops a nonlinear optimization model for the optimal allocation of labor and investment resources in a three-sector open economy. The model is based on the Cobb–Douglas production function and incorporates sectoral interdependencies, capital depreciation, trade balances, and import quotas. The resource allocation problem is formalized as a constrained optimization task, solved analytically using the Lagrange multipliers method and numerically via the golden section search. The model is calibrated using real statistical data from Kazakhstan (2010–2022), an open resource-exporting economy. The results identify structural thresholds that define balanced growth conditions and resource-efficient configurations. Compared to existing studies, the proposed model uniquely integrates external trade constraints with analytical solvability, filling a methodological gap in the literature. The developed framework is suitable for medium-term planning under stable external conditions and enables sensitivity analysis under alternative scenarios such as sanctions or price shocks. Limitations include the assumption of stationarity and the absence of dynamic or stochastic features. Future research will focus on dynamic extensions and applications in other open economies. Full article

This article is devoted to the study of the possibilities for improvAzing the quality of energy management systems adopted at open-pit mining enterprises in the Russian Federation. The main idea of the work is to apply stochastic boundary value analysis methods using the production function for individual and integral estimates of the performance of energy-consuming objects when performing various types of technological work. It is shown that mining enterprises are experiencing problems in the field of rational energy consumption due to the lack of strictly formalized ways to determine the frontiers of the efficiency value of the parameter of specific energy consumption (SEC). A justification is given for the need to apply stochastic frontier analysis (SFA) methods and use the Cobb–Douglas production function to account for the nonlinearity and stochasticity of the operating conditions of energy-consuming mining objects. The results of a statistical analysis of the data on the operation of EKG-10 excavators at operating enterprises in Siberia are presented, as well as an assessment of their energy efficiency using the adopted approach based on planning the target value of SEC. The results of computational experiments on constructing an energy efficiency model using the SFA/Cobb–Douglas function for various data segmentation options are presented. Computational experiments have been conducted to compare variants based on the Cobb–Douglas production function and translog function with semi-normal and exponential distribution forms for the same data set. A comparative assessment is given of the approaches to the complex analysis of activities adopted at enterprises and proposed in this study, characterizing potential hidden energy losses in the range from 4.53% to 20.73%. Full article