Search Results (2)

This paper critically examines the persistent limitations of spatial planning reforms in China in addressing urban–rural integration, despite significant and successive legislative and planning reforms. Through a historically grounded and institutionally informed analysis, the study traces the evolution of China’s planning regimes across three key phases—urban planning, urban–rural planning, and territorial spatial planning (TSP)—highlighting shifting policy logics and the enduring structural challenges that shape rural marginalization. Drawing on national planning documents and authors’ empirical insights from planning practice, the paper identifies four interrelated and persistent constraints: (1) cross-scalar and interdepartmental fragmentation in governance, (2) contradictions in the land system that restrict rural development rights, (3) fiscal dependence on land conversion that distorts planning priorities, and (4) technical and conceptual gaps that reduce rural planning to physicalist and exogenous interventions. The paper contributes by offering a periodized account of China’s rural planning reforms, situating these within global debates on rural marginalization, and evaluating the transformative potential of the TSP framework. It argues that achieving meaningful urban–rural integration requires a fundamental rethinking of planning as a developmental, rather than solely regulatory, practice—one that is territorially embedded, socially responsive, and functionally aligned with endogenous rural revitalization. Full article

This work aims to improve the reliability of dynamic systems by eliminating the effect of random control variables. At first, the reliability-based dynamic optimization problem (RB-DOP) is introduced and defined to account for dynamic systems with uncertainty associated with random control variables. Whereafter, in order to solve RB-DOP efficiently, the constraint function response shift scalar (CFRSS)-based RB-DOP optimization method is proposed, in which the nested RB-DOP is decoupled into an equivalent deterministic DOP and a CFRSS search problem, and the two problems are addressed iteratively until the control law converges. Specifically, the shift scalar CFRSS is calculated by the probability density function of the constraint function response and deducted for probabilistic constraints in the constraint function response space to move the violated constraints toward the reliable region, avoiding solving large-scale optimization problems in the control variable space. Finally, two numerical examples and a low-thrust orbit transfer problem are investigated to demonstrate the feasibility of the proposed approach. Full article