A fuzzy goal programming approach to analyse sustainable development goals of India

Nomani, Mohammad Asim; Ali, Irfan; Fügenschuh, Armin; Ahmed, Aquil

doi:10.1080/13504851.2016.1200178

Cited by 29 publications

(13 citation statements)

References 10 publications

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“…Taking uncertainty into consideration, some researchers studied the topic on sustainability. Nomani et al [27] utilized fuzzy goal programming to analyse environmental, energy and sustainability goals of India by the year 2030 with reference to the key economic sectors of India. Jayaraman et al [19] studied the sustainable development of UAE by the year 2030 considering economy, population, energy and environment by fuzzy goal programming.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing sustainable development problem under uncertainty: Robust vs fuzzy optimization methods

Jia

Bai

Song

et al. 2019

IFS

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Sustainable development problem involves several conflicting criteria on economy, energy, environment and social aspects and some sources of uncertainty due to its attribute. It is necessary to mitigate risks in sustainable development schedule. However, the existing literature includes limited quantitative research on robust strategies for sustainable development under uncertainty. Under these concerns, this paper presents a robust multi-objective optimization formulation for allocating labor across economic sectors to simultaneously satisfy economy (gross domestic product, GDP), environment (greenhouse gas (GHG) emissions), energy (electricity) and society (labor), in which the per capita GDP, per capita electricity consumption, per capita GHG and per capita rate of unemployment are robust uncertainty. There are three conflicting objectives in our sustainable development problem. The first objective maximizes the sectoral GDP, the second objective minimizes the sectoral electricity consumption and the third objective minimizes the sectoral GHG emissions. We adapt-constraint method to deal with the multiple objectives for the sustainable development problem, and obtain a more flexible result via an interactive decision-making process. Since uncertainty has often led to computationally intractable models, we reformulate the proposed model using robust optimization method into the tractable robust counterpart (RC) forms under two types of uncertainty sets. Finally, to demonstrate the effectiveness and applicability for our model, we conduct a case study for meeting year 2030 sustainable development of the United Arab Emirates (UAE). The numerical results show: (a) the robust multi-objective model is effective in uncertain environment and provides a reliable decision tool than deterministic model for integrated multi-objective sustainable development problem; (b) when the possibility distributions of uncertain parameters are available, fuzzy optimization model can provide better decision-making than robust model under box uncertainty set.

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Section: Literature Reviewmentioning

confidence: 99%

Optimizing sustainable development problem under uncertainty: Robust vs fuzzy optimization methods

Jia

Bai

Song

et al. 2019

IFS

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“…Some key points of India's INDC report [22] are the following: As a measurement of sustainable development, we focus on GDP growth, electricity consumption, GHG emissions and employment across different economic activities of India. As defined in [12], we use the following nine sectors in our FGP model: Here, x i represents the number of employees in sector i. Table 6 and Figures 4-6 show the sector-wise contribution of the GDP, electricity consumption, GHG emissions and the number of employees.…”

Section: India's Indc Review Reportmentioning

confidence: 99%

“…Jayaraman et al [7][8][9][10][11] developed FGP models and weighted FGP models that integrate different sectors of the UAE and provide a view of how much resources should be allocated to different sectors simultaneously to achieve SDGs on GDP growth, electricity consumption and GHG emissions in the UAE. The work in Nomani et al [12] proposed an FGP model to analyze the SDGs of India by the year 2030 with reference to the key economic sectors of India. Schult et al [13] suggested mixed-integer linear programming methods to solve large-scale input-output systems that describe an optimal allocation of the world's resources to operate the global economy in a more sustainable way.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Criteria Goal Programming Model to Analyze the Sustainable Goals of India

2018

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There is an ever-growing demand for sustainable development (SD) plans, in order to foster a country's economic growth by implementing suitable policies and initiative programs for the development of the primary, the secondary and the tertiary sectors. We present a multi-criteria modeling approach using the linear programming problem (LPP) framework for a simultaneous optimization of these three sectors. Furthermore, we develop a fuzzy goal programming (FGP) model that provides an optimal allocation of resources by achieving future goals on the gross domestic product (GDP), the electricity consumption (EC) and the greenhouse gas (GHG) emissions. Furthermore, a weighted model of FGP is presented to obtain varying solutions according to the priorities set by the decision-maker for achieving future goals of GDP growth, EC and GHG emissions. The presented models provide useful insight for decision-makers when implementing strategies across different sectors. As a model country, we chose India by the year 2030. A study of economic policies and sustainable development goals (SDGs) for India is finally carried out.

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“…More recently, a study about global sustainability of all European Union countries using Fuzzy Goal Programming methodologies has been proposed in Vié et al (2018). Nomani et al (2017) implemented a Fuzzy Goal Programming approach to evaluate the satisfaction of sustainability policy targets in India. Omrani, Valipour and Emrouznejad created a weighted Goal Programming model to plan efficiently regional sustainable development and workforce allocation in Iran, see Omrani et al (2018).…”

Section: Introductionmentioning

confidence: 99%

“…Nomani et al. ( 2017 ) implemented a Fuzzy Goal Programming approach to evaluate the satisfaction of sustainability policy targets in India. Omrani, Valipour and Emrouznejad created a weighted Goal Programming model to plan efficiently regional sustainable development and workforce allocation in Iran, see Omrani et al.…”

Section: Introductionmentioning

confidence: 99%

Sustainability, cooperation and mobility of workers within and between European countries: a two-stage goal programming model

2020

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Facing multiple and often considered as conflicting stakes, either economical, migratory, or environmental, policy-making may struggle to identify and implement relevant policy action allowing for balanced and joint completion of such challenges. Addressing this important public issue, we develop a multi-criteria two-stage Goal Programming (GP) model to identify optimal policy paths towards the Europe 2020 strategy on economic growth, employment levels and environmental sustainability. The model is calibrated on current contributions of economic sectors in all European countries to each policy objective: contribution to economic output (GDP), emissions of Green House Gas, electric consumption and number of jobs. First, we study the optimal allocation of workers within economic sectors of each European country to maximize the joint achievement of Europe 2020 multi criteria sustainability targets. We then extend the model to allow cooperation between states, namely allowing internal migrations of workers between countries. We highlight how supranational allocation schemes of surplus workers improve the satisfaction of national sustainability objectives. Finally, we consider extra-European migrants regional integration and study the consequences of such opening over EU2020 targets satisfaction and per capita GDP. Simulation results highlight countries performance comparison, and sheds light on significant benefits from such cooperation for the majority of countries. Improved integration of internal and external workforce generally improves the achievement of EU2020 objectives, while keeping per capita GDP at least constant. Moreover, we expose the relevance of cooperative work-flows allocation strategies across Europe and emphasize the importance of workers mobility in order to ensure more sustainable common development.

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A fuzzy goal programming approach to analyse sustainable development goals of India

Cited by 29 publications

References 10 publications

Optimizing sustainable development problem under uncertainty: Robust vs fuzzy optimization methods

Optimizing sustainable development problem under uncertainty: Robust vs fuzzy optimization methods

A Multi-Criteria Goal Programming Model to Analyze the Sustainable Goals of India

Sustainability, cooperation and mobility of workers within and between European countries: a two-stage goal programming model

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