Planning sustainable development through a scenario-based stochastic goal programming model

Most real-world optimization problems involve numerous conflicting criteria, imprecise information estimates and goals, thus the stochastic goal programming method offers an analytical framework to model and solve such problems. In this paper, we develop a stochastic goal programming model with satisfaction function that integrates optimal resource (labor) allocation to simultaneously satisfy conflicting criteria related to economic development, energy consumption, workforce allocation, and greenhouse gas emissions. We validate the model using sectorial data obtained from diverse sources on vital economic sectors for the United Arab Emirates. The results offer significant insights to decision makers for strategic planning decisions and investment allocations towards achieving long term sustainable development goals.