Spatial and temporal evolution characteristics of eco-environment index.

Reprinted from [(http://www.resdc.cn/DOI),2023.DOI:10.12078/2023010101] under a CC BY license, with permission from [Xu Xinliang], original copyright [January 2023].</p

Memetic algorithm with route decomposing for periodic capacitated arc routing problem

In this paper, the Periodic Capacitated Arc Routing Problem (PCARP) is investigated. PCARP is an extension of the well-known CARP from a single period to a multi-period horizon. In PCARP, two objectives are to be minimized. One is the number of required vehicles (nv), and the other is the total cost (tc). Due to the multi-period nature, given the same graph or road network, PCARP can have a much larger solution space than the single-period CARP counterpart. Furthermore, PCARP consists of an additional allocation sub-problem (of the days to serve the arcs), which is interdependent with the routing sub-problem. Although some attempts have been made for solving PCARP, more investigations are yet to be done to further improve their performance especially on large-scale problem instances. It has been shown that optimizing nv and tc separately (hierarchically) is a good way of dealing with the two objectives. In this paper, we further improve this strategy and propose a new Route Decomposition (RD) operator thereby. Then, the RD operator is integrated into a Memetic Algorithm (MA) framework for PCARP, in which novel crossover and local search operators are designed accordingly. In addition, to improve the search efficiency, a hybridized initialization is employed to generate an initial population consisting of both heuristic and random individuals. The MA with RD (MARD) was evaluated and compared with the state-of-the-art approaches on two benchmark sets of PCARP instances and a large data set which is based on a real-world road network. The experimental results suggest that MARD outperforms the compared state-of-the-art algorithms, and improves most of the best-known solutions. The advantage of MARD becomes more obvious when the problem size increases. Thus, MARD is particularly effective in solving large-scale PCARP instances. Moreover, the efficacy of the proposed RD operator in MARD has been empirically verified. Graphical abstract https://ars.els-cdn.com/content/image/1-s2.0-S1568494616304768-fx1_lrg.jpg © This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0

Spatial distribution map of study area.

Reprinted from [(http://www.resdc.cn/DOI),2023.DOI:10.12078/2023010103] under a CC BY license, with permission from [Xu Xinliang], original copyright [January 2023]. Reprinted from [(http://www.resdc.cn/DOI),2023.DOI:10.12078/2023010101] under a CC BY license, with permission from [Xu Xinliang], original copyright [January 2023].</p

Dynamic evolution of coupling and coordinated development between urbanization and eco-environment in the Chengdu-Chongqing urban agglomeration from 2001 to 2020.

Dynamic evolution of coupling and coordinated development between urbanization and eco-environment in the Chengdu-Chongqing urban agglomeration from 2001 to 2020.</p

The mechanism of interaction between urbanization and eco-environment.

The mechanism of interaction between urbanization and eco-environment.</p

Variance decomposition of urbanization on the eco-environment.

Variance decomposition of urbanization on lnES. (b) Variance decomposition of urbanization on lnEP. (c) Variance decomposition of urbanization on lnER.</p

Subsystem and indicator weights for urbanization and environment.

Subsystem and indicator weights for urbanization and environment.</p

Cointegration and eigenvalue test results.

Urban agglomerations are emerging as new regional units for national participation in global competition and the international division of labor. However, they face increasingly severe resource and eco-environment pressures during urbanization. The coordination of the relationship between urbanization and the eco-environment has attracted global attention. In this study, we used Coupling Coordination Degree and Vector Autoregression models to examine the dynamic evolution, coupling relationships, coordinated development patterns, and interaction mechanisms between urbanization and the eco-environment. The results indicate that: (1) The level of urbanization in the Chengdu-Chongqing Urban agglomeration was relatively low, and the region showed a good eco-environment background. However, rapid urbanization is gradually straining the carrying capacity of the eco-environment. (2) A close and stable coupling relationship exists between urbanization and the eco-environment, which has reached an advanced coupling stage. The status of coordinated development among cities differs considerably, and multiple stable forms may exist simultaneously. (3) Urbanization has a substantial impact on environmental changes, whereas the restrictive effect of the eco-environment on urbanization development is not particularly notable. (4) Various interactive relationships exist between the urbanization and eco-environment subsystems, including positive promotion and negative constraint effects. The positive promotion effect mainly manifests between the economic, social, and ecological response subsystems, while the negative constraint effect is most evident in the mutual coercion and inhibition between the regional urbanization, economic urbanization, ecological status, and ecological pressure subsystems. These findings have important policy implications for decision makers exploring the path of coordinated and sustainable development in urbanization and the eco-environment in Urban agglomerations.</div

Granger causality analysis results.

Urban agglomerations are emerging as new regional units for national participation in global competition and the international division of labor. However, they face increasingly severe resource and eco-environment pressures during urbanization. The coordination of the relationship between urbanization and the eco-environment has attracted global attention. In this study, we used Coupling Coordination Degree and Vector Autoregression models to examine the dynamic evolution, coupling relationships, coordinated development patterns, and interaction mechanisms between urbanization and the eco-environment. The results indicate that: (1) The level of urbanization in the Chengdu-Chongqing Urban agglomeration was relatively low, and the region showed a good eco-environment background. However, rapid urbanization is gradually straining the carrying capacity of the eco-environment. (2) A close and stable coupling relationship exists between urbanization and the eco-environment, which has reached an advanced coupling stage. The status of coordinated development among cities differs considerably, and multiple stable forms may exist simultaneously. (3) Urbanization has a substantial impact on environmental changes, whereas the restrictive effect of the eco-environment on urbanization development is not particularly notable. (4) Various interactive relationships exist between the urbanization and eco-environment subsystems, including positive promotion and negative constraint effects. The positive promotion effect mainly manifests between the economic, social, and ecological response subsystems, while the negative constraint effect is most evident in the mutual coercion and inhibition between the regional urbanization, economic urbanization, ecological status, and ecological pressure subsystems. These findings have important policy implications for decision makers exploring the path of coordinated and sustainable development in urbanization and the eco-environment in Urban agglomerations.</div

Coupling relationship and coordinated development types between urbanization and eco-environment in the Chengdu-Chongqing urban agglomeration.

Coupling relationship and coordinated development types between urbanization and eco-environment in the Chengdu-Chongqing urban agglomeration.</p