| Abstrakt: |
This paper introduces a novel Time-Cost Trade-Off Optimization Model (TCTOM) tailored for retrofitting projects in densely populated areas like India. Integrating structural, electrical, plumbing, HVAC, fire protection, insulation, and finishing aspects, the TCTOM utilizes Multi-Objective Genetic Algorithms (MOGAs) to identify Pareto-optimal solutions, balancing project duration and cost while meeting functional requirements and budget constraints. Through a case study in Gwalior, India, the TCTOM demonstrates practical applicability, offering decision support for stakeholders. Additionally, a comparison with existing methods such as MOPSO, MOACO, and MOTLBO highlights the superior performance of the proposed MOGA algorithm in terms of convergence and diversity of optimal solutions. The MOGA strikes an effective balance between convergence and diversity, producing a diverse set of high-quality solutions along the Pareto-optimal front within a reasonable computational time. Overall, the TCTOM, coupled with MOGA, provides a valuable tool for optimizing retrofitting projects, advancing sustainability and resilience in urban development initiatives. |
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