Citation:

Aravindh Balan , 2026. "Sustainability Metrics and Optimization Techniques for Industrial Infrastructure ", ESP Journal of Engineering & Technology Advancements  6(1): 99-109.

Abstract:

An integral component of a sustainable urban transformation is the creation of sustainable infrastructure. Sustainable industrial infrastructure is essential for promoting long-term economic growth with the least amount of environmental damage and the greatest amount of social well-being. The conventional infrastructure development methods have been quite focused in most cases on productivity and cost effectiveness without considering the overall sustainability implications providing sustainability metrics and optimization in regards to industrial infrastructure systems. It focuses on the systematization of environmental, economic, and social indicators of sustainability into decision-making based on high-level optimization frameworks sustainable design and operation systems, such as energy-saving systems, waste energy reuse, integration of renewable energy, and digital technologies, Artificial Intelligence (AI), Internet of Things (IoT), and Digital Twins (DTs). The use of mathematical, heuristic, metaheuristic, and data-driven optimization methods as effective in contributing to multi-objective sustainability the role of Multi-Criteria Decision-Making (MCDM) methods in solving trade-offs between competing sustainability objectives. Optimization based on AI, energy-based evaluation, and hybrid models of industrial infrastructure. The results underline the fact that a connection between sustainability measures and optimization models can facilitate the creation of a system of resource-intensive, resilient, and environmentally-friendly industrial infrastructure, which will be able to sustain the industry transformation.

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Keywords:

Sustainable Industrial Infrastructure, Multi-Objective Optimization, Artificial Intelligence, Energy-Efficient Systems, Decision-Making Models.