A New Application for the Goal Programming—The Target Decision Rule for Uncertain Problems

Approach for Village Carbon Emissions Index and Planning Strategies Generation Based on Two-Stage Optimization Models

With the implementation of China’s rural revitalization strategy, the social economy of villages is expected to fully develop; however, their carbon emissions must be controlled within a reasonable range. Realization of this goal is part of the guidance and control of village planning. Clarifying the coupling relationship between village land uses and rural carbon emissions is fundamental for low-carbon village planning. In this study, by exploring the relationships between carbon emissions factors, land-use types, and human activities, the reference range of carbon emissions coefficients for various land-use types in rural areas is obtained. Then, based on the interval values of carbon emissions coefficients, a two-stage optimization model for village carbon emissions analysis is established, which is used to generate the minimal value of village carbon emissions and planning schemes to achieve different carbon emissions target values. First, the smallest carbon emissions value for a certain village is obtained based on a linear programming model. Then, to analyze the planning scheme possibilities under different carbon emissions targets, an objective planning model (including various parameters) is constructed. Through this two-stage optimization model, the optimal planning scheme is set and corresponding planning indicators under different scenarios are obtained through a sensitivity analysis. Combined with a case study in Dongzhuang Village, Shanghai, the results indicate that, with continuous improvement of the basic national carbon emissions database, the range of carbon emissions coefficients for typical local land uses can be determined, and the carbon emissions and land-use types of villages can be co-planned using the two-stage optimization model. With the proposed model, the range of carbon emissions for villages and scenario analysis results considering carbon emissions values associated with various land-use planning schemes can be obtained, contributing greatly to low-carbon village planning.

From Goal Programming for Continuous Multi-Criteria Optimization to the Target Decision Rule for Mixed Uncertain Problems

Goal programming (GP) is applied to the discrete and continuous version of multi-criteria optimization. Recently, some essential analogies between multi-criteria decision making under certainty (M-DMC) and scenario-based one-criterion decision making under uncertainty (1-DMU) have been revealed in the literature. The aforementioned similarities allow the adjustment of GP to an entirely new domain. The aim of the paper is to create a new decision rule for mixed uncertain problems on the basis of the GP methodology. The procedure can be used by pessimists, optimists and moderate decision makers. It is designed for one-shot decisions. One of the significant advantages of the novel approach is related to the possibility to analyze neutral criteria, which are not directly taken into account in existing classical procedures developed for 1-DMU.