A Multi-Objective Optimization of Physical Activity Spaces

Fang Wei, Wenwen Xu and Chen Hua ()
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Fang Wei: College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
Wenwen Xu: College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
Chen Hua: College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China

Land, 2022, vol. 11, issue 11, 1-17

Abstract: Optimizing the location of physical activity spaces (PAS) to ensure health, equity and efficiency has long been an important issue in urban planning. Given the health benefits of urban green spaces (UGS), taking Gongshu District in Hangzhou as a case, we examine the issue of where such PAS should be located to optimize three objectives: (1) minimize the distance between PAS and UGS; (2) maximize the accessibility of PAS and (3) maximize the population that falls within the coverage range. This study develops a multi-objective optimization of physical activity spaces model (MOPAS) based upon multi-objective particle swarm optimization to yield a set of non-dominated Pareto optimum solutions that can be used to determine the most practical tradeoffs between the conflicting objectives. It compares the advantages and disadvantages of the Pareto solutions and evaluates the construction situation of locations and the implementation feasibility. Decision-makers can choose the best solution according to subjective preferences and objective conditions. The MOPSO holds great promise for improving the location optimization of PAS and the methods applied can be adapted to support multi-objective optimization of facilities in urban planning globally.

Keywords: physical activity spaces; urban green spaces; location optimization; multi-objective particle swarm optimization algorithm (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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