Modeling 3E-S sustainable development problem by an ambiguous chance constrained optimization method

Ruru Jia

doi:10.1016/j.eswa.2024.124993

2024-12-01

PRE

Ruru Jia

Gao, Jinwu

Wen He *

DOI：10.1016/j.eswa.2024.124993

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The environmental-energy-economic-social (3E-S) sustainable development problem aims to balance the environment, energy, and economy upon which human society critically relies. However, it is further complicated by various ambiguous input parameters about greenhouse gas (GHG) emissions, electricity consumption, gross domestic product (GDP), and unemployment rate. To address this complexity, this paper develops an ambiguous chance constrained optimization model with multiple chance soft constraints for optimizing the 3E- S sustainable development problem by strategically allocating labor across key sectors. Tractable formulations of the proposed model are derived by constructing three types of ambiguity sets for input parameters with ambiguous probability distributions. The first is to construct support-mean ambiguous distribution sets with little known information, the second is to extend support-mean ambiguity sets to mean-covariance ambiguity sets by incorporating interactive relationships among sectors, and the third is to extend support-mean ambiguity sets to inner-outer ambiguity sets with Wasserstein metric from globalized distributionally robust perspective. The availability and computability of the proposed model have been illustrated by planning India's 3E-S sustainability for the year 2030. The results suggest that (i) the proposed method exhibits the capability to offer flexible policy measures; (ii) India should prioritize the development of the Mining and quarrying sector, , the Transport, storage, communication, and services sector, , and the Constructions sector; ; (iii) India needs to make greater efforts for promoting GDP while controlling GHG emissions and energy consumption; (iv) The policy measures and objectives are influenced by tolerance levels, support intervals, interactive relationships among sectors, globalized sensitivity, and Wasserstein ball size.

Keyword:

3E-S sustainable development

Multiple criteria

Ambiguous chance constraints

Distributionally robust optimization

Globalized distributionally robust optimization