Sustainable Ecosystem Planning Based on Discrete Stochastic Dynamic Programming and Evolutionary Game Theory

TL;DR

This paper introduces a novel approach combining discrete stochastic dynamic programming and evolutionary game theory to optimize sustainable ecosystem planning, with a focus on water management in China's Loess Plateau.

Contribution

It develops a new SDP model emphasizing ecosystem transition probabilities and integrates game theory for multi-user impact analysis in ecological resource planning.

Findings

Optimal strategies for ecological resource management identified.

Impacts of user decisions on ecosystem sustainability analyzed.

Application demonstrated in water resource planning on Loess Plateau.

Abstract

This paper proposed a discrete stochastic dynamic programming (SDP) model for sustainable ecosystem (SE) planning of the Loess Plateau in Northwestern, China, and analyzed the ecological resource planning by the evolutionary game model in the decision-making process. The main objective is to explore a new approach of SE planning from a viewpoint of discrete SDP and evolutionary game theory, with a specific application in the area of ecological resource planning such as water management problems. In contrast to previous work, the proposed SDP method focuses on the transition probability matrix of the ecosystem in a statistic sense, and uses the DP algorithm to obtain the optimal ecological resource planning strategies among multi-subsystems, then analyzes impacts of decision between different users. Firstly, the application background and the concept of SE planning are introduced. Then, a brief overview of existing theory for analyzing sustainable ecosystem is presented. Furthermore, a SDP-based mathematical model and its application to water resource planning of central areas of Loess Plateau are presented as an example. Finally, supplementary analysis of impacts between different users in SE planning as a game playing is provided.