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Reinforcement learning for sustainable construction scheduling: a many-objective framework with adaptive search and multi-criteria decision support

Delivering construction projects sustainably requires reconciling duration, cost, carbon emissions and the stability and utilization of site resources, yet these objectives conflict and the choice among candidate schedules is seldom made on an explicit, data-driven basis. This study aims to develop a data-driven de...

A. Mohy, Haytham Sanad · 0 citations
Aug 2026

Fuzzy 5D multi objectives optimization of construction planning using game theory for automated time cost quality resource and workspace resolution

This study aims to develop a five-dimensional (5D) optimization framework to resolve spatial and resource conflicts in construction scheduling. By integrating resource leveling and workspace congestion with the traditional time, cost and quality objectives, the research addresses the critical gap between theoretica...

A. Mohy, Haytham Sanad · 0 citations
Dec 2026

Automated Decision Intelligence Framework for Infrastructure Project Scheduling via Seven-Dimensional Many-Objective Evolutionary Optimization and OPA-TOPSIS Ranking

The management of complex infrastructure projects necessitates the simultaneous optimization of multiple competing objectives beyond the traditional time, cost, and quality triangle. This study proposes a seven-dimensional multiobjective scheduling framework integrating duration, cost, quality, resource leveling, env...

A. Mohy · 0 citations
Review Aug 2026

An integrated machine-learning approach for classifying severe incident risk in maritime construction using weather and operational data

This study develops a data-driven severity-classification approach for maritime construction, relating equipment activity from incident narratives to localized hydro-meteorological conditions to complement static safety systems to complement static safety systems.

A. Mohy · 0 citations

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