Abstract
Urbanization has become a main challenge all over developing countries in the 21st Century. However, decision making should take into account the different national situations with their complex factors to achieve sustainable development. As standards of living have risen in urban areas, local/neighbor urbanization has become a coming trend in China. With this in mind, the paper focuses on the optimization of nearby gathered village locations in Population Migration (PM) with consideration of both qualitative and quantitative criteria. Therefore, an integrated multiple objective decision making approach (MODM) under a bi-uncertain environment is proposed to solve this problem, which is based on the comprehensive Economy-Society-Ecology-Resource-Religion (ESERR) urbanization concept. The first step is to establish a bi-uncertain multiple objective programming model orienting the problem. Secondly, the model process is composed of fuzzy random variable transformation and the expected value model based on a new fuzzy measure, which is given accordingly to obtain the equivalent model. Thirdly, in order to describe the model efficiently, the Multi-Objective Adaptive Global Local Neighbor Particle Swarm Optimization (MOAGLNPSO) with three-dimensional Pareto optimal judgment criteria is designed. Finally, a case study is tested to validate the effectiveness and to illustrate the advantages of the whole approach. This novel approach can help optimize sustainable urbanization strategies and ensure their realistic application.
Highlights
Urbanization has been brought into focus in most developing countries
This study investigates how these challenges can be overcome by an integrated Multiple Objective Decision Making (MODM) approach under a bi-uncertain environment to optimize the gathered village location problem
The literature we have studied can be divided into four aspects: (1) sustainable urbanization; (2) Village location Problem (VLP); (3) MODM methods; (4) uncertainty and solution algorithm
Summary
Urbanization has been brought into focus in most developing countries. China has its own characteristic urbanization road, since its history of development is different from other developing countries and developed countries. According to the Department of Economic and Social Affairs of the United Nations [2], more and more Chinese will live in cities in 2050 This change in population distribution resulting from the movement of people from rural to urban areas matches the definition of urbanization [3]. With the high living density in China’s urban areas, local/neighbor urbanization is the most effective approach for sustainable development. This is a way for the rural population not to migrate to large or medium-sized cities, but to nearby small cities and towns. The lifestyle of the migrant has been improved with the productivity improvement, income growth and life quality promotion Under these circumstances, confirming the gathered area locations of PM seems much more important. The literature we have studied can be divided into four aspects: (1) sustainable urbanization; (2) VLP; (3) MODM methods; (4) uncertainty and solution algorithm
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